Python 2.7.16 |Anaconda, Inc.| (default, Sep 24 2019, 16:55:38)
Type "copyright", "credits" or "license" for more information.
IPython 5.8.0 -- An enhanced Interactive Python.
? -> Introduction and overview of IPython's features.
%quickref -> Quick reference.
help -> Python's own help system.
object? -> Details about 'object', use 'object??' for extra details.
In [1]: runfile('/Users/lester/Documents/GitHub/kelly_model/scenario29/update_GBeagle_fix/true_constant_alpha/mass_sfr_z_correction/alpha_beta_covprop/random_start_gmm/random_start/bad_gmm_cuts/kelly_MH_GMM_3d_Hogg_constant_beta_constant_alpha.py', wdir='/Users/lester/Documents/GitHub/kelly_model/scenario29/update_GBeagle_fix/true_constant_alpha/mass_sfr_z_correction/alpha_beta_covprop/random_start_gmm/random_start/bad_gmm_cuts')
435
266
task_manager
task_manager
task_manager
initial_guess
initial_guess
initial_guess
task_manager
initial_guess
run_mcmc
_initialize_chains
_step
_get_Rhat
_get_psi
INITIAL GUESSES 0.8603618557948427 0.0 1.0150310484183036 0.0 0.43680641718574476 1.0 0.229166666667 -0.4609759673362414 3.3848112460971858
INITIAL GUESSES 0.5866818546597699 0.0 0.7323360903664308 0.0 0.3996339435829777 1.0 0.228070175439 -0.2993867113994893 3.2168053947906308
step
step
INITIAL GUESSES 0.6034983548093563 0.0 0.6983298627011384 0.0 0.3754780741090389 1.0 0.286343612335 0.22075428097912525 2.421174237327158
INITIAL GUESSES 0.9247275629974878 0.0 1.0492959614153001 0.0 0.42250871361282566 1.0 0.175213675214 -0.4060474872456063 3.8679457839628113
step
step
zeta acceptanceProb 0 0 185 -995.3256338877243 5.405762959381243 0.0
0
0
0
0
/Users/lester/Documents/GitHub/kelly_model/scenario29/update_GBeagle_fix/true_constant_alpha/mass_sfr_z_correction/alpha_beta_covprop/random_start_gmm/random_start/bad_gmm_cuts/kelly_MH_GMM_3d_Hogg_constant_beta_constant_alpha.py:597: RuntimeWarning: divide by zero encountered in log10
scatter1 = ax1.scatter(self.xi[idx_z_bin][idx_sort], self.eta[idx_z_bin][idx_sort], c=np.log10((z_good/z_bad)[idx_sort]), cmap=mpl.cm.get_cmap('coolwarm'), alpha=1.0, vmin=-2.5, vmax=2.5, s=100)
/opt/anaconda2/lib/python2.7/site-packages/matplotlib/cbook/deprecation.py:107: MatplotlibDeprecationWarning: Passing one of 'on', 'true', 'off', 'false' as a boolean is deprecated; use an actual boolean (True/False) instead.
warnings.warn(message, mplDeprecation, stacklevel=1)
/opt/anaconda2/lib/python2.7/site-packages/matplotlib/cbook/deprecation.py:107: MatplotlibDeprecationWarning: Passing one of 'on', 'true', 'off', 'false' as a boolean is deprecated; use an actual boolean (True/False) instead.
warnings.warn(message, mplDeprecation, stacklevel=1)
/opt/anaconda2/lib/python2.7/site-packages/matplotlib/cbook/deprecation.py:107: MatplotlibDeprecationWarning: Passing one of 'on', 'true', 'off', 'false' as a boolean is deprecated; use an actual boolean (True/False) instead.
warnings.warn(message, mplDeprecation, stacklevel=1)
/opt/anaconda2/lib/python2.7/site-packages/matplotlib/cbook/deprecation.py:107: MatplotlibDeprecationWarning: Passing one of 'on', 'true', 'off', 'false' as a boolean is deprecated; use an actual boolean (True/False) instead.
warnings.warn(message, mplDeprecation, stacklevel=1)
/Users/lester/Documents/GitHub/kelly_model/scenario29/update_GBeagle_fix/true_constant_alpha/mass_sfr_z_correction/alpha_beta_covprop/random_start_gmm/random_start/bad_gmm_cuts/kelly_MH_GMM_3d_Hogg_constant_beta_constant_alpha.py:646: RuntimeWarning: divide by zero encountered in log10
scatter2 = ax2.scatter(self.xi[idx_z_bin][idx_sort], self.eta[idx_z_bin][idx_sort], c=np.log10((z_good/z_bad)[idx_sort]), cmap=mpl.cm.get_cmap('coolwarm'), alpha=1.0, vmin=-2.5, vmax=2.5, s=100)
Traceback (most recent call last):
File "/opt/anaconda2/lib/python2.7/site-packages/IPython/core/formatters.py", line 334, in __call__
return printer(obj)
File "/opt/anaconda2/lib/python2.7/site-packages/IPython/core/pylabtools.py", line 247, in <lambda>
png_formatter.for_type(Figure, lambda fig: print_figure(fig, 'png', **kwargs))
File "/opt/anaconda2/lib/python2.7/site-packages/IPython/core/pylabtools.py", line 131, in print_figure
fig.canvas.print_figure(bytes_io, **kw)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/backend_bases.py", line 2212, in print_figure
**kwargs)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/backends/backend_agg.py", line 517, in print_png
FigureCanvasAgg.draw(self)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/backends/backend_agg.py", line 437, in draw
self.figure.draw(self.renderer)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/artist.py", line 55, in draw_wrapper
return draw(artist, renderer, *args, **kwargs)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/figure.py", line 1493, in draw
renderer, self, artists, self.suppressComposite)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/image.py", line 141, in _draw_list_compositing_images
a.draw(renderer)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/artist.py", line 55, in draw_wrapper
return draw(artist, renderer, *args, **kwargs)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/axes/_base.py", line 2635, in draw
mimage._draw_list_compositing_images(renderer, self, artists)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/image.py", line 141, in _draw_list_compositing_images
a.draw(renderer)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/artist.py", line 55, in draw_wrapper
return draw(artist, renderer, *args, **kwargs)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/legend.py", line 775, in draw
bbox = self._legend_box.get_window_extent(renderer)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/offsetbox.py", line 266, in get_window_extent
w, h, xd, yd, offsets = self.get_extent_offsets(renderer)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/offsetbox.py", line 388, in get_extent_offsets
for c in self.get_visible_children()]
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/offsetbox.py", line 259, in get_extent
w, h, xd, yd, offsets = self.get_extent_offsets(renderer)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/offsetbox.py", line 458, in get_extent_offsets
for c in self.get_visible_children()]
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/offsetbox.py", line 259, in get_extent
w, h, xd, yd, offsets = self.get_extent_offsets(renderer)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/offsetbox.py", line 388, in get_extent_offsets
for c in self.get_visible_children()]
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/offsetbox.py", line 259, in get_extent
w, h, xd, yd, offsets = self.get_extent_offsets(renderer)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/offsetbox.py", line 458, in get_extent_offsets
for c in self.get_visible_children()]
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/offsetbox.py", line 831, in get_extent
bbox, info, d = self._text._get_layout(renderer)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/text.py", line 309, in _get_layout
ismath=ismath)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/backends/backend_agg.py", line 236, in get_text_width_height_descent
s, fontsize, renderer=self)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/texmanager.py", line 501, in get_text_width_height_descent
dvifile = self.make_dvi(tex, fontsize)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/texmanager.py", line 362, in make_dvi
with Locked(self.texcache):
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/cbook/__init__.py", line 2529, in __enter__
raise self.TimeoutError(err_str)
TimeoutError: LOCKERROR: matplotlib is trying to acquire the lock
'/Users/lester/.matplotlib/tex.cache/.matplotlib_lock-*'
and has failed. This maybe due to any other process holding this
lock. If you are sure no other matplotlib process is running try
removing these folders and trying again.
<Figure size 576x576 with 4 Axes>
/Users/lester/Documents/GitHub/kelly_model/scenario29/update_GBeagle_fix/true_constant_alpha/mass_sfr_z_correction/alpha_beta_covprop/random_start_gmm/random_start/bad_gmm_cuts/kelly_MH_GMM_3d_Hogg_constant_beta_constant_alpha.py:1186: RuntimeWarning: divide by zero encountered in log
prob_arr[j] = np.log(self.piBeagle[i,j])+multivariate_normal.logpdf(values,mean,cov)
zeta acceptanceProb 0 3 185 -1447.2842725865985 4.818998735219411 0.0
/Users/lester/Documents/GitHub/kelly_model/scenario29/update_GBeagle_fix/true_constant_alpha/mass_sfr_z_correction/alpha_beta_covprop/random_start_gmm/random_start/bad_gmm_cuts/kelly_MH_GMM_3d_Hogg_constant_beta_constant_alpha.py:1186: RuntimeWarning: divide by zero encountered in log
prob_arr[j] = np.log(self.piBeagle[i,j])+multivariate_normal.logpdf(values,mean,cov)
/Users/lester/Documents/GitHub/kelly_model/scenario29/update_GBeagle_fix/true_constant_alpha/mass_sfr_z_correction/alpha_beta_covprop/random_start_gmm/random_start/bad_gmm_cuts/kelly_MH_GMM_3d_Hogg_constant_beta_constant_alpha.py:1186: RuntimeWarning: divide by zero encountered in log
prob_arr[j] = np.log(self.piBeagle[i,j])+multivariate_normal.logpdf(values,mean,cov)
/Users/lester/Documents/GitHub/kelly_model/scenario29/update_GBeagle_fix/true_constant_alpha/mass_sfr_z_correction/alpha_beta_covprop/random_start_gmm/random_start/bad_gmm_cuts/kelly_MH_GMM_3d_Hogg_constant_beta_constant_alpha.py:1186: RuntimeWarning: divide by zero encountered in log
prob_arr[j] = np.log(self.piBeagle[i,j])+multivariate_normal.logpdf(values,mean,cov)
zeta acceptanceProb 0 8 185 -3386.332678085653 3.8359589108743 0.0
zeta acceptanceProb 0 3 185 -915.7532768983751 4.671336426038637 0.0
zeta acceptanceProb 0 5 185 -2448.447556644241 4.802407305999505 0.0
zeta acceptanceProb 0 6 185 -854.01406250732 3.6686784220605757 0.0
zeta acceptanceProb 0 6 32 -1089.4172225256061 5.799434141632341 0.0
zeta acceptanceProb 0 6 185 -778.4822585314021 5.263150657850925 0.0
zeta acceptanceProb 0 13 185 -1172.052179656629 4.349509082243963 0.0
zeta acceptanceProb 0 8 185 -1800.821036483153 5.269307407766707 0.0
zeta acceptanceProb 0 9 32 -802.3327202335643 5.760249629647013 0.0
zeta acceptanceProb 0 9 185 -1263.9434632687432 2.905836948789327 0.0
zeta acceptanceProb 0 9 32 -897.5312921563279 4.557414684323234 0.0
zeta acceptanceProb 0 15 185 -813.0076060220072 4.787443977852454 0.0
zeta acceptanceProb 0 10 32 -1294.7807643261701 6.25378587383778 0.0
zeta acceptanceProb 0 10 185 -745.0101510180432 1.4997817959163822 0.0
zeta acceptanceProb 0 11 32 -1601.632719462496 6.251768252675688 0.0
zeta acceptanceProb 0 12 185 -924.4437002917306 4.221772980974228 0.0
zeta acceptanceProb 0 14 185 -790.9059439437266 0.11736229922710706 0.0
zeta acceptanceProb 0 14 185 -873.9761812398036 4.131195794279461 0.0
zeta acceptanceProb 0 21 185 -1499.3967614780147 2.1478841114681844 0.0
zeta acceptanceProb 0 17 185 -934.2950168121902 4.9371534306755755 0.0
zeta acceptanceProb 0 17 32 -1111.521995643291 5.372106780705715 0.0
zeta acceptanceProb 0 18 185 -1624.194901888282 4.937148034249377 0.0
zeta acceptanceProb 0 19 32 -1259.786422606485 6.7860804684964 0.0
zeta acceptanceProb 0 19 32 -1241.0842138447458 4.575752231472906 0.0
zeta acceptanceProb 0 26 185 -1639.011392476988 4.696018529731169 0.0
zeta acceptanceProb 0 29 185 -1637.8859316503872 4.510968948237651 0.0
zeta acceptanceProb 0 24 32 -1153.8230312865708 6.002493292825111 0.0
zeta acceptanceProb 0 30 185 -3721.3241837903165 4.946916631382811 0.0
zeta acceptanceProb 0 32 185 -859.9094510989175 3.662174976017726 0.0
zeta acceptanceProb 0 33 185 -2325.5656632702585 3.3858838725263807 0.0
zeta acceptanceProb 0 28 185 -869.6806316125802 0.7765428526348925 0.0
zeta acceptanceProb 0 29 185 -1738.0606345971319 4.9187855855612135 0.0
zeta acceptanceProb 0 31 185 -3457.336298001551 4.528331711578698 0.0
zeta acceptanceProb 0 32 1 -832.8061891367357 3.5666314209084264 0.0
zeta acceptanceProb 0 33 185 -961.0001878133609 0.9402322777111016 0.0
zeta acceptanceProb 0 39 185 -1314.2817599074776 3.1361773974787117 0.0
zeta acceptanceProb 0 34 185 -2246.2226702883727 5.044870397350197 0.0
zeta acceptanceProb 0 34 185 -1073.4416068361854 3.503846482436985 0.0
zeta acceptanceProb 0 40 185 -754.6511937281343 2.9251480393899247 0.0
zeta acceptanceProb 0 35 185 -1564.8058148215478 5.044866556145966 0.0
zeta acceptanceProb 0 36 185 -1400.9873625951777 4.450992256558662 0.0
zeta acceptanceProb 0 44 185 -777.8684682613256 3.449844675876268 0.0
zeta acceptanceProb 0 39 185 -748.512560973609 4.2956909094464315 0.0
zeta acceptanceProb 0 40 32 -1137.8772047464377 2.584367070535068 0.0
zeta acceptanceProb 0 40 185 -843.9522137393998 4.426733568379246 0.0
zeta acceptanceProb 0 41 185 -753.5883153913851 4.099059940296943 0.0
zeta acceptanceProb 0 49 185 -3282.617259716678 4.475828688130294 0.0
zeta acceptanceProb 0 44 185 -1763.7479917465598 2.6409236527775115 0.0
zeta acceptanceProb 0 45 61 -878.3690889325892 1.3407527807762336 0.0
zeta acceptanceProb 0 45 185 -814.9730544947413 3.559471243706495 0.0
zeta acceptanceProb 0 45 185 -1048.5462479420328 4.12415962846978 0.0
zeta acceptanceProb 0 46 185 -940.0322694689834 3.9890859973352297 0.0
zeta acceptanceProb 0 46 185 -3096.6318420811253 3.7906284615922363 0.0
zeta acceptanceProb 0 47 185 -1014.1356511302062 3.9598499190938288 0.0
zeta acceptanceProb 0 50 185 -2022.48281534864 4.678367813834871 0.0
zeta acceptanceProb 0 56 32 -1580.5287589478642 4.189985093482273 0.0
zeta acceptanceProb 0 56 185 -1011.9763540398295 4.564357802955684 0.0
zeta acceptanceProb 0 52 185 -821.0784884792204 0.9338675257162916 0.0
zeta acceptanceProb 0 53 185 -773.7508693458824 3.658416571886945 0.0
zeta acceptanceProb 0 53 185 -950.6530266585655 3.8763766986523382 0.0
zeta acceptanceProb 0 61 185 -1022.028334540124 2.2298457796864755 0.0
zeta acceptanceProb 0 56 185 -1346.8578326961479 4.687898880901257 0.0
zeta acceptanceProb 0 62 32 -988.3618509150003 5.781784761718214 0.0
zeta acceptanceProb 0 64 185 -1126.6612303405423 2.2943387334835204 0.0
zeta acceptanceProb 0 59 185 -1707.8797573501697 4.5079910412062425 0.0
zeta acceptanceProb 0 65 32 -882.811321633171 6.279742686286429 0.0
zeta acceptanceProb 0 60 185 -1526.6290048797914 4.541139896996706 0.0
zeta acceptanceProb 0 61 185 -1018.6197409675807 4.666289421250476 0.0
zeta acceptanceProb 0 64 185 -1138.538101423226 4.744920084210717 0.0
zeta acceptanceProb 0 71 32 -860.327523727463 5.715941263087846 0.0
zeta acceptanceProb 0 68 185 -1704.5467047267516 4.24146713492976 0.0
zeta acceptanceProb 0 68 185 -753.4800345386036 4.412688621225665 0.0
zeta acceptanceProb 0 70 185 -870.0882292772912 3.2420747212147187 0.0
zeta acceptanceProb 0 76 185 -1049.0059589121634 2.2523433936485504 0.0
zeta acceptanceProb 0 77 61 -831.342854090739 4.464847152685545 0.0
zeta acceptanceProb 0 72 185 -1125.7629656668569 4.516778854207049 0.0
xi acceptanceProb 0 75 211 -1812.283666045575 4.554915350503854 0.0
zeta acceptanceProb 0 75 211 -4007.920587593246 5.194037501662939 0.0
zeta acceptanceProb 0 82 185 -763.3628942909229 4.262515693079508 0.0
zeta acceptanceProb 0 77 185 -1007.3516543542644 3.56407240993627 0.0
zeta acceptanceProb 0 77 185 -1222.7188654196746 3.6371221374509 0.0
xi acceptanceProb 0 77 211 -2469.134507138638 5.74333078662021 0.0
zeta acceptanceProb 0 84 32 -1140.4356814428818 4.566552905870886 0.0
zeta acceptanceProb 0 79 185 -1583.743362779094 4.520096333909857 0.0
zeta acceptanceProb 0 85 185 -1035.4678023274525 2.7482730602915217 0.0
zeta acceptanceProb 0 85 185 -1030.846963020938 3.86397151861457 0.0
zeta acceptanceProb 0 87 185 -785.3339497901228 3.7974891365025973 0.0
zeta acceptanceProb 0 87 185 -1007.0880310920094 2.967624234661987 0.0
zeta acceptanceProb 0 93 32 -1159.580686541536 -0.48585481977287837 0.0
zeta acceptanceProb 0 88 185 -1048.7873172050013 2.1843074858629126 0.0
zeta acceptanceProb 0 88 185 -807.1974202485409 2.95483582698386 0.0
zeta acceptanceProb 0 89 32 -2659.2464406822874 6.35975845815627 0.0
zeta acceptanceProb 0 91 185 -830.1987325125284 3.563502101418604 0.0
zeta acceptanceProb 0 91 185 -2896.6733042622586 3.8579186150091713 0.0
zeta acceptanceProb 0 92 32 -860.3473476950554 6.458807262800529 0.0
zeta acceptanceProb 0 93 185 -744.2530674345412 3.0554593249339828 0.0
zeta acceptanceProb 0 99 185 -991.3560048931266 5.031165870905075 0.0
zeta acceptanceProb 0 95 185 -787.1433159907407 1.6037646852685987 0.0
zeta acceptanceProb 0 95 32 -846.0574668829744 3.9218507073118674 0.0
zeta acceptanceProb 0 100 185 -1034.9797305040315 4.756081991129237 0.0
zeta acceptanceProb 0 96 185 -903.788240883804 1.6037677576122502 0.0
zeta acceptanceProb 0 102 185 -1304.7366967410712 5.025532290882454 0.0
zeta acceptanceProb 0 98 185 -3552.7396164463057 1.6037842215704678 0.0
zeta acceptanceProb 0 103 185 -765.4995946543919 5.0255273183190425 0.0
zeta acceptanceProb 0 99 185 -799.6694677636427 3.142080215935273 0.0
zeta acceptanceProb 0 101 185 -1011.5079135788395 4.123447364003466 0.0
zeta acceptanceProb 0 108 32 -888.5676711278701 2.0387114922329994 0.0
zeta acceptanceProb 0 104 185 -1648.6800013945233 2.6487904134136366 0.0
zeta acceptanceProb 0 104 185 -4038.6793042520576 5.035263336871775 0.0
zeta acceptanceProb 0 105 185 -749.4699796144605 2.6296113968934796 0.0
zeta acceptanceProb 0 105 185 -1328.293215213004 4.003629629580676 0.0
xi acceptanceProb 0 107 80 -937.7948391064609 -0.3298365268628567 0.0
zeta acceptanceProb 0 108 185 -2482.780047221469 2.643296438990993 0.0
zeta acceptanceProb 0 109 185 -836.4623458540269 2.8028647776296776 0.0
zeta acceptanceProb 0 110 185 -886.4062980326845 2.6220192002334723 0.0
zeta acceptanceProb 0 115 185 -1470.699105246081 5.0475325537081215 0.0
zeta acceptanceProb 0 111 32 -1755.6747613135249 5.880100314603367 0.0
zeta acceptanceProb 0 111 185 -1627.69468299004 1.924721503742882 0.0
zeta acceptanceProb 0 116 185 -4591.6567043832865 4.75681859312791 0.0
zeta acceptanceProb 0 113 185 -1813.4164795239462 4.702630038728075 0.0
zeta acceptanceProb 0 115 185 -3012.350281175252 2.743997013294649 0.0
zeta acceptanceProb 0 122 185 -1975.73035838023 4.649406916640041 0.0
zeta acceptanceProb 0 119 185 -1239.6802978239032 3.6323242679789627 0.0
zeta acceptanceProb 0 120 185 -2290.261154737752 2.280934752426699 0.0
zeta acceptanceProb 0 125 185 -1780.642834299265 3.469878797418946 0.0
zeta acceptanceProb 0 120 185 -1541.8250377201355 5.3188777007739345 0.0
zeta acceptanceProb 0 121 32 -990.2304680567897 5.201481933261702 0.0
zeta acceptanceProb 0 124 185 -1675.330938965862 1.674128935766431 0.0
zeta acceptanceProb 0 130 185 -1031.2157754590971 3.2815364407728222 0.0
zeta acceptanceProb 0 126 185 -2555.691963565493 5.130904087105259 0.0
zeta acceptanceProb 0 129 185 -1137.2673377505114 -0.40165550945737705 0.0
eta acceptanceProb 0 134 234 -779.4462168856958 4.935849875642526 0.0
zeta acceptanceProb 0 133 61 -757.1488807711985 3.6740816491691066 0.0
zeta acceptanceProb 0 133 185 -2226.5257094753324 4.366005461011078 0.0
zeta acceptanceProb 0 134 185 -921.3514985895707 3.061800610189949 0.0
zeta acceptanceProb 0 135 32 -1273.6132770708552 2.1799873148127884 0.0
zeta acceptanceProb 0 138 185 -1539.6230915311967 4.701624762777822 0.0
zeta acceptanceProb 0 141 32 -909.9550502064504 4.642220379755871 0.0
zeta acceptanceProb 0 141 185 -887.403242336218 1.6380054939530337 0.0
zeta acceptanceProb 0 143 185 -829.3493589040052 3.339145215758835 0.0
zeta acceptanceProb 0 143 32 -848.7553944944564 2.697513549672707 0.0
zeta acceptanceProb 0 143 185 -921.317291168485 3.2593100005636755 0.0
zeta acceptanceProb 0 145 185 -1177.1711218735825 -0.7265686812973922 0.0
zeta acceptanceProb 0 159 185 -753.7012962190878 4.400771178088281 0.0
zeta acceptanceProb 0 156 32 -1966.039875423791 6.406324853711361 0.0
zeta acceptanceProb 0 157 185 -845.3816011873135 3.9437366933826117 0.0
zeta acceptanceProb 0 167 32 -1000.5810867032405 1.6520541891340037 0.0
zeta acceptanceProb 0 168 185 -1002.8120292198728 3.742408741371555 0.0
zeta acceptanceProb 0 166 61 -1061.0744397532387 2.8597747938641103 0.0
zeta acceptanceProb 0 166 32 -1112.4662864808251 4.916022716966147 0.0
zeta acceptanceProb 0 166 185 -2546.232427393495 5.122698920836555 0.0
zeta acceptanceProb 0 172 185 -785.0806232395664 4.0903099381576045 0.0
zeta acceptanceProb 0 168 185 -921.8841579239875 2.9533346111472856 0.0
zeta acceptanceProb 0 168 185 -1118.74841412651 2.7600434275289953 0.0
zeta acceptanceProb 0 174 185 -1239.5554324910754 4.09521942207537 0.0
zeta acceptanceProb 0 178 185 -1718.6713955545779 4.086397000619926 0.0
zeta acceptanceProb 0 174 185 -934.673290422986 2.336931759418489 0.0
zeta acceptanceProb 0 179 185 -2296.334699409838 3.9787773444765007 0.0
zeta acceptanceProb 0 174 185 -1148.5475627567753 2.260840323022212 0.0
zeta acceptanceProb 0 177 61 -1413.483677061565 4.269311503527547 0.0
zeta acceptanceProb 0 181 185 -1523.9085489822503 4.343356080654024 0.0
zeta acceptanceProb 0 186 185 -2995.2971185392794 3.016668590878548 0.0
zeta acceptanceProb 0 182 185 -1090.109931110361 4.309379586045261 0.0
zeta acceptanceProb 0 185 32 -1074.9370344559757 6.193657667262531 0.0
zeta acceptanceProb 0 186 32 -2215.974989053342 6.192095439033027 0.0
zeta acceptanceProb 0 193 185 -931.3616917381217 3.388404632096518 0.0
eta acceptanceProb 0 198 234 -774.5659363407706 5.0110534895859224 0.0
zeta acceptanceProb 0 202 32 -1655.6773137312118 6.738535349015189 0.0
zeta acceptanceProb 0 197 185 -2097.733843919682 2.5881653525092094 0.0
zeta acceptanceProb 0 198 185 -768.2001799004624 2.405524832592402 0.0
zeta acceptanceProb 0 204 32 -1625.5555936747571 6.628950354325734 0.0
zeta acceptanceProb 0 200 185 -1037.4718182184643 5.287983922010126 0.0
zeta acceptanceProb 0 206 185 -1509.4886327142306 1.007165996792299 0.0
zeta acceptanceProb 0 201 185 -801.6349346218033 5.287982521230815 0.0
zeta acceptanceProb 0 202 185 -922.1452723858619 0.5666181718441758 0.0
zeta acceptanceProb 0 209 32 -801.7550298030212 6.2045482358780735 0.0
zeta acceptanceProb 0 205 185 -789.8362447585541 0.9321152220623707 0.0
zeta acceptanceProb 0 206 185 -2967.8486330740507 4.867736480396222 0.0
zeta acceptanceProb 0 211 32 -2338.2023441678616 6.371942093352997 0.0
zeta acceptanceProb 0 211 185 -1077.7401546267097 -0.642038405280263 0.0
zeta acceptanceProb 0 210 185 -1081.5390239484059 3.8908828304960483 0.0
zeta acceptanceProb 0 210 32 -1525.9133693910944 6.073029555837424 0.0
zeta acceptanceProb 0 217 185 -1175.9987795882357 0.5163712630885944 0.0
zeta acceptanceProb 0 212 185 -828.3256675219756 5.053262334442493 0.0
zeta acceptanceProb 0 213 32 -1589.9841738274945 6.387290446045401 0.0
zeta acceptanceProb 0 214 185 -803.600324330235 2.3821387229764763 0.0
zeta acceptanceProb 0 214 32 -1235.6634253720558 6.510880491638423 0.0
zeta acceptanceProb 0 220 185 -1601.5798284694085 0.6577382285904605 0.0
zeta acceptanceProb 0 216 185 -3551.8402508827166 2.671386009584286 0.0
zeta acceptanceProb 0 221 32 -879.2403957204488 6.202336994820941 0.0
zeta acceptanceProb 0 217 185 -4362.7006318949525 3.572209277725381 0.0
zeta acceptanceProb 0 219 32 -3155.403439749604 5.328074337079571 0.0
zeta acceptanceProb 0 219 185 -958.4703314469015 3.0857735381071696 0.0
zeta acceptanceProb 0 222 185 -859.4704605250205 2.9158452194835833 0.0
zeta acceptanceProb 0 222 185 -1599.864291790912 4.722723993419516 0.0
zeta acceptanceProb 0 229 185 -1033.3580860017464 2.4917533777558285 0.0
zeta acceptanceProb 0 225 185 -1258.2610485492496 5.014176948853168 0.0
zeta acceptanceProb 0 227 185 -1084.146702265151 2.7904159038395626 0.0
zeta acceptanceProb 0 229 185 -4192.873334063608 4.168751795587005 0.0
zeta acceptanceProb 0 229 185 -1174.0465152690076 4.102343884156904 0.0
zeta acceptanceProb 0 231 185 -1172.1744311946768 4.245751205709196 0.0
zeta acceptanceProb 0 236 185 -1437.0236563150595 3.0957135559380218 0.0
zeta acceptanceProb 0 232 61 -778.0941513427096 4.194231451460098 0.0
zeta acceptanceProb 0 232 185 -1110.1264639278954 4.559450428489419 0.0
zeta acceptanceProb 0 233 185 -768.1542470242981 4.559444518176985 0.0
zeta acceptanceProb 0 234 32 -980.475251767109 6.126578213012289 0.0
zeta acceptanceProb 0 243 185 -1569.421454989648 3.235698884831286 0.0
zeta acceptanceProb 0 240 185 -947.7268961000761 4.533076196778291 0.0
zeta acceptanceProb 0 249 185 -3058.828415909498 3.7291178715156885 0.0
zeta acceptanceProb 0 253 185 -1109.0774572104767 1.5102811970842747 0.0
zeta acceptanceProb 0 249 185 -1075.9636899061552 3.6828311719913995 0.0
zeta acceptanceProb 0 249 185 -933.8604181816037 4.110871277612474 0.0
zeta acceptanceProb 0 250 185 -1464.5178112799294 4.53666748006922 0.0
zeta acceptanceProb 0 250 185 -1109.6561773893318 4.65467378612195 0.0
zeta acceptanceProb 0 252 185 -903.0598169162037 2.203177706809976 0.0
zeta acceptanceProb 0 257 32 -1105.4659386925555 6.39387820807293 0.0
zeta acceptanceProb 0 257 185 -917.857438290485 1.9092705442185913 0.0
zeta acceptanceProb 0 254 32 -987.0700976910238 6.218942261968456 0.0
zeta acceptanceProb 0 254 185 -978.811448910141 3.0396898557580823 0.0
zeta acceptanceProb 0 255 185 -1840.579763285625 2.5170756073339486 0.0
zeta acceptanceProb 0 257 185 -2031.7874084696718 3.978908127973638 0.0
zeta acceptanceProb 0 258 185 -1227.6240632475597 3.4471989710614634 0.0
zeta acceptanceProb 0 263 185 -847.9900279903659 -0.33257373063763307 0.0
zeta acceptanceProb 0 259 185 -2159.704188592141 4.011909219808466 0.0
zeta acceptanceProb 0 260 185 -1939.9745760187204 4.29036440530449 0.0
zeta acceptanceProb 0 260 185 -988.7267066588819 4.532067521207724 0.0
zeta acceptanceProb 0 261 185 -1099.1496624053505 4.5830642618182695 0.0
zeta acceptanceProb 0 261 185 -2740.779089576808 4.60565855881833 0.0
zeta acceptanceProb 0 262 185 -2057.6064507764117 1.2076489334585943 0.0
zeta acceptanceProb 0 267 185 -816.9571180429595 2.694134080928433 0.0
zeta acceptanceProb 0 263 185 -2165.660376736318 1.9494302367083085 0.0
zeta acceptanceProb 0 264 185 -1095.5420304904294 2.7232446318533197 0.0
zeta acceptanceProb 0 265 185 -1051.813693792895 4.0823088461604815 0.0
zeta acceptanceProb 0 266 185 -782.334920933739 3.3689088219218615 0.0
zeta acceptanceProb 0 266 185 -1031.0809527196777 4.1657548840311485 0.0
zeta acceptanceProb 0 267 185 -762.8025477658341 4.3429664922915805 0.0
zeta acceptanceProb 0 267 32 -953.8370282302898 6.06478590509433 0.0
zeta acceptanceProb 0 268 185 -3279.371759576542 1.5143971398879756 0.0
zeta acceptanceProb 0 269 32 -1862.6221010104296 6.1844693394933925 0.0
zeta acceptanceProb 0 271 185 -1459.8448339397928 4.773295937028012 0.0
zeta acceptanceProb 0 276 185 -1131.455266574648 2.7759885961571125 0.0
zeta acceptanceProb 0 272 32 -1161.6802756052293 1.0641788233077767 0.0
zeta acceptanceProb 0 272 32 -1214.6908860402464 5.705743995097327 0.0
zeta acceptanceProb 0 273 185 -1195.7306948386072 4.926441544420744 0.0
zeta acceptanceProb 0 279 185 -1143.97016371675 1.5888500089144122 0.0
zeta acceptanceProb 0 275 32 -775.4685213053226 5.708997003425361 0.0
zeta acceptanceProb 0 276 32 -1472.2746039497745 5.252706840073285 0.0
zeta acceptanceProb 0 277 32 -1557.4446209689581 4.152880790484616 0.0
zeta acceptanceProb 0 277 185 -1224.5339861611196 4.592401134286629 0.0
zeta acceptanceProb 0 277 32 -1599.9316880573272 5.575749723292966 0.0
zeta acceptanceProb 0 279 32 -790.2071518051578 4.200078558327861 0.0
zeta acceptanceProb 0 279 185 -1432.2782061076623 4.040378433832764 0.0
zeta acceptanceProb 0 282 185 -1661.260711153828 3.867875624629052 0.0
zeta acceptanceProb 0 283 32 -1245.0426018684125 5.631356951289599 0.0
zeta acceptanceProb 0 284 185 -946.5985263755699 4.856743364907441 0.0
zeta acceptanceProb 0 284 185 -866.4612303144637 3.4163670125019414 0.0
zeta acceptanceProb 0 285 185 -1363.9698121223419 4.856751747953067 0.0
zeta acceptanceProb 0 291 185 -927.597363954523 2.975690205633664 0.0
zeta acceptanceProb 0 287 185 -878.2029042390091 4.561706749729629 0.0
zeta acceptanceProb 0 289 185 -1199.1216248396586 4.048386929983353 0.0
zeta acceptanceProb 0 290 32 -781.7509273287172 6.7186003148135764 0.0
zeta acceptanceProb 0 296 61 -1118.8067081519616 4.086470124233392 0.0
zeta acceptanceProb 0 296 185 -1651.4003266152245 2.1938620718984945 0.0
zeta acceptanceProb 0 292 185 -890.0274901857158 3.813127205691624 0.0
zeta acceptanceProb 0 295 185 -1486.584853159895 2.358475965095463 0.0
zeta acceptanceProb 0 296 32 -1247.8768184161684 6.469634723335248 0.0
zeta acceptanceProb 0 296 185 -762.5744753391596 3.3754442557560482 0.0
zeta acceptanceProb 0 300 32 -943.83647622259 5.673034840816687 0.0
zeta acceptanceProb 0 300 185 -845.4438185906845 2.1909014245232976 0.0
zeta acceptanceProb 0 305 185 -1756.6276935324552 1.866817582290155 0.0
zeta acceptanceProb 0 302 32 -1694.785093690802 5.074696351186469 0.0
zeta acceptanceProb 0 307 185 -823.7853732715356 1.943760332342491 0.0
zeta acceptanceProb 0 308 185 -1411.5017843375256 2.9339876903978377 0.0
zeta acceptanceProb 0 309 185 -1061.3243242287256 2.732227652092341 0.0
zeta acceptanceProb 0 313 32 -831.215353394854 5.849800635907657 0.0
zeta acceptanceProb 0 315 185 -784.7380870232629 3.972240216348303 0.0
zeta acceptanceProb 0 316 32 -870.8072385673033 5.904593069690027 0.0
zeta acceptanceProb 0 315 185 -774.5278977369559 0.3587759459783664 0.0
zeta acceptanceProb 0 316 185 -1826.3834144775647 4.273007748781178 0.0
zeta acceptanceProb 0 318 32 -1676.6365161638996 3.9930366981028635 0.0
zeta acceptanceProb 0 319 185 -1528.0930166284181 3.2175329329085316 0.0
zeta acceptanceProb 0 321 185 -1394.958993249742 1.8287373051154163 0.0
zeta acceptanceProb 0 322 185 -1598.8127521386189 4.554860824562193 0.0
xi acceptanceProb 0 328 234 -816.4523698362963 1.9906478001251635 0.0
zeta acceptanceProb 0 324 185 -2318.140298289489 1.300571779965325 0.0
zeta acceptanceProb 0 325 185 -1566.2527932331022 2.2210855427933764 0.0
zeta acceptanceProb 0 325 185 -1111.8095469818068 1.2787634704270365 0.0
zeta acceptanceProb 0 333 185 -769.2210055099094 5.044978408694403 0.0
zeta acceptanceProb 0 338 185 -1017.270889414123 3.839904443942685 0.0
zeta acceptanceProb 0 336 32 -1232.130690813853 4.858265494422882 0.0
zeta acceptanceProb 0 336 32 -1700.4285519689936 5.898764592617633 0.0
zeta acceptanceProb 0 336 185 -745.418700234593 2.2808346575190592 0.0
zeta acceptanceProb 0 340 185 -973.9121554501661 3.874123251400744 0.0
zeta acceptanceProb 0 339 32 -1018.6506223642887 5.734288802092152 0.0
zeta acceptanceProb 0 339 185 -1447.7099233509457 2.0105342963556656 0.0
zeta acceptanceProb 0 341 185 -1114.9845336727126 2.875231569407913 0.0
zeta acceptanceProb 0 350 185 -1667.1605355761567 2.612984097119085 0.0
zeta acceptanceProb 0 351 185 -1191.7030827093167 1.8967057544834702 0.0
zeta acceptanceProb 0 352 32 -1898.4354036999619 3.6861660893826187 0.0
zeta acceptanceProb 0 351 185 -745.3068930104948 0.5030405796580593 0.0
zeta acceptanceProb 0 353 185 -1807.3913509981035 3.36029088408562 0.0
zeta acceptanceProb 0 357 185 -1006.133451252349 2.912420901521895 0.0
zeta acceptanceProb 0 354 185 -780.2563047526139 2.0439997244003774 0.0
zeta acceptanceProb 0 355 185 -1790.441678394541 3.003424238869819 0.0
zeta acceptanceProb 0 362 185 -1104.219916279992 -0.8204124784202822 0.0
zeta acceptanceProb 0 360 185 -787.7408022508254 2.55703881293535 0.0
zeta acceptanceProb 0 360 185 -774.3119701228225 2.138928711210121 0.0
zeta acceptanceProb 0 364 185 -1117.5804559329445 1.0717749191369879 0.0
zeta acceptanceProb 0 361 32 -4479.274045178179 5.034078154324982 0.0
zeta acceptanceProb 0 364 185 -1240.284528147031 2.6476314287765375 0.0
zeta acceptanceProb 0 365 185 -908.7529799691724 4.497402812116388 0.0
zeta acceptanceProb 0 370 185 -1706.416389826597 2.245908651716531 0.0
zeta acceptanceProb 0 368 185 -942.4750706189714 4.644311914608769 0.0
zeta acceptanceProb 0 371 185 -1594.832289799025 3.6180282853905057 0.0
zeta acceptanceProb 0 372 185 -1145.9842165158966 3.5537536208346046 0.0
zeta acceptanceProb 0 372 185 -2425.022544692579 2.854851225896396 0.0
zeta acceptanceProb 0 373 185 -1106.7247355367633 3.5537327084994086 0.0
zeta acceptanceProb 0 376 185 -746.2051765537747 4.397258392410221 0.0
zeta acceptanceProb 0 381 185 -2703.930098496468 4.525681455827467 0.0
zeta acceptanceProb 0 386 185 -1084.9491756040468 2.151037801568328 0.0
zeta acceptanceProb 0 389 185 -4437.288307020688 4.530691370140334 0.0
zeta acceptanceProb 0 394 185 -807.548190407456 2.0369226596361156 0.0
zeta acceptanceProb 0 394 185 -3909.4144176148784 4.582585260173651 0.0
zeta acceptanceProb 0 400 32 -881.9343923261576 5.024913677902934 0.0
zeta acceptanceProb 0 398 185 -825.427104612322 4.169552136193368 0.0
zeta acceptanceProb 0 402 32 -814.3494595504708 2.3815496803326046 0.0
zeta acceptanceProb 0 401 185 -940.0680071173933 4.380693146947221 0.0
zeta acceptanceProb 0 402 185 -1012.5502053048453 2.4168047909675834 0.0
zeta acceptanceProb 0 406 185 -850.9655155853203 2.012593349702518 0.0
zeta acceptanceProb 0 403 185 -1478.8846419108202 3.538183291359903 0.0
zeta acceptanceProb 0 407 185 -3977.133403009303 3.4924452389403777 0.0
zeta acceptanceProb 0 408 185 -785.7376468370838 3.4924405980191753 0.0
zeta acceptanceProb 0 411 32 -891.5036113065373 6.575820811144498 0.0
zeta acceptanceProb 0 411 185 -1193.1591446243276 3.4260563835654 0.0
zeta acceptanceProb 0 412 185 -741.648114381148 4.268056907059554 0.0
zeta acceptanceProb 0 414 32 -841.7086252455287 5.675301390081701 0.0
zeta acceptanceProb 0 414 185 -1706.0658723556985 3.209919355996849 0.0
zeta acceptanceProb 0 413 185 -1177.231215540732 2.6128348695971937 0.0
zeta acceptanceProb 0 415 185 -1383.6413750154363 3.329067704760613 0.0
zeta acceptanceProb 0 417 185 -1000.0155158454044 4.439040098146045 0.0
zeta acceptanceProb 0 421 185 -766.3580853687715 3.179537398069831 0.0
eta acceptanceProb 0 420 234 -746.8293454029493 3.6873798417577888 0.0
zeta acceptanceProb 0 422 32 -924.3174491538348 6.088619498513538 0.0
zeta acceptanceProb 0 423 32 -2209.527461669995 5.890424663485932 0.0
zeta acceptanceProb 0 429 185 -1387.961560017712 1.7885081724956713 0.0
zeta acceptanceProb 0 427 185 -753.7909567056573 2.7683313242624785 0.0
zeta acceptanceProb 0 436 32 -1092.0168454269308 6.747281637626688 0.0
zeta acceptanceProb 0 435 32 -956.1098182962007 5.689763013280215 0.0
xi acceptanceProb 0 441 234 -817.750651616336 1.6393639450325903 0.0
zeta acceptanceProb 0 441 32 -1111.6366063797318 6.251248454865477 0.0
zeta acceptanceProb 0 442 185 -1443.9945243838226 3.015682941292089 0.0
zeta acceptanceProb 0 450 211 -996.5001475586997 2.416279306252686 0.0
zeta acceptanceProb 0 447 185 -1291.3222334175641 2.6166186158191014 0.0
xi acceptanceProb 0 451 211 -1701.3635517192154 1.8052005743276682 0.0
zeta acceptanceProb 0 452 211 -2224.8460547013224 2.165765240761281 0.0
zeta acceptanceProb 0 449 32 -1647.842515295094 5.932607519923425 0.0
zeta acceptanceProb 0 450 185 -1245.414305163811 3.223990406153879 0.0
zeta acceptanceProb 0 452 185 -755.069158329333 3.5582121839998706 0.0
zeta acceptanceProb 0 454 32 -990.0263529205754 5.866306717721566 0.0
zeta acceptanceProb 0 453 185 -2445.859514201362 5.426348177126297 0.0
zeta acceptanceProb 0 455 32 -1576.7013431849145 5.9665387641522845 0.0
zeta acceptanceProb 0 459 32 -1151.160724623531 6.313691623089402 0.0
zeta acceptanceProb 0 457 185 -1248.0148937832994 2.3447938475518475 0.0
zeta acceptanceProb 0 461 185 -1068.8782404787507 2.1201259292791956 0.0
zeta acceptanceProb 0 460 61 -758.9775554791945 3.9996152316197513 0.0
zeta acceptanceProb 0 462 32 -1005.1658574817131 5.979060711782075 0.0
zeta acceptanceProb 0 468 32 -833.65442247857 5.522384652527451 0.0
zeta acceptanceProb 0 464 185 -2928.674077555765 3.3019119535991006 0.0
zeta acceptanceProb 0 466 185 -1659.3075691343486 3.7054416302326216 0.0
zeta acceptanceProb 0 471 32 -1061.828828179872 5.86023478802454 0.0
zeta acceptanceProb 0 469 32 -787.2310932905108 5.523517072118651 0.0
zeta acceptanceProb 0 469 185 -947.498489573972 3.496498459561575 0.0
zeta acceptanceProb 0 474 32 -852.56712858003 4.036316368721396 0.0
zeta acceptanceProb 0 471 185 -1436.2245542669646 -0.2996985608139071 0.0
zeta acceptanceProb 0 475 32 -3340.841852254421 4.034144798355106 0.0
zeta acceptanceProb 0 476 32 -1623.1971849040362 3.2723442258805306 0.0
zeta acceptanceProb 0 475 185 -1032.3624743992461 4.759701096047349 0.0
zeta acceptanceProb 0 480 185 -826.7250141270428 2.7896289223062065 0.0
zeta acceptanceProb 0 478 185 -1142.8929901538052 3.6514407295761035 0.0
zeta acceptanceProb 0 478 32 -1095.6715726771538 4.684493981618182 0.0
zeta acceptanceProb 0 481 185 -1210.084535907693 0.17006086177559387 0.0
zeta acceptanceProb 0 484 32 -789.1229672118221 3.255457338203686 0.0
zeta acceptanceProb 0 484 185 -1057.1941693116923 5.220094308280517 0.0
zeta acceptanceProb 0 488 32 -1715.9428117557786 5.863057876274775 0.0
zeta acceptanceProb 0 488 32 -2737.6659395996408 5.375463854733345 0.0
zeta acceptanceProb 0 490 185 -767.858096494963 5.502735752673122 0.0
zeta acceptanceProb 0 493 185 -3133.3058823957294 3.952739842481712 0.0
zeta acceptanceProb 0 494 185 -901.4825810868023 4.2909727673068945 0.0
zeta acceptanceProb 0 494 185 -1053.4949139245387 5.303230054004276 0.0
500
zeta acceptanceProb 0 496 185 -1369.1658113609706 4.593475910952568 0.0
500
/Users/lester/Documents/GitHub/kelly_model/scenario29/update_GBeagle_fix/true_constant_alpha/mass_sfr_z_correction/alpha_beta_covprop/random_start_gmm/random_start/bad_gmm_cuts/kelly_MH_GMM_3d_Hogg_constant_beta_constant_alpha.py:597: RuntimeWarning: divide by zero encountered in log10
scatter1 = ax1.scatter(self.xi[idx_z_bin][idx_sort], self.eta[idx_z_bin][idx_sort], c=np.log10((z_good/z_bad)[idx_sort]), cmap=mpl.cm.get_cmap('coolwarm'), alpha=1.0, vmin=-2.5, vmax=2.5, s=100)
500
/Users/lester/Documents/GitHub/kelly_model/scenario29/update_GBeagle_fix/true_constant_alpha/mass_sfr_z_correction/alpha_beta_covprop/random_start_gmm/random_start/bad_gmm_cuts/kelly_MH_GMM_3d_Hogg_constant_beta_constant_alpha.py:646: RuntimeWarning: divide by zero encountered in log10
scatter2 = ax2.scatter(self.xi[idx_z_bin][idx_sort], self.eta[idx_z_bin][idx_sort], c=np.log10((z_good/z_bad)[idx_sort]), cmap=mpl.cm.get_cmap('coolwarm'), alpha=1.0, vmin=-2.5, vmax=2.5, s=100)
500
/opt/anaconda2/lib/python2.7/site-packages/scipy/stats/_distn_infrastructure.py:1745: RuntimeWarning: divide by zero encountered in double_scalars
x = np.asarray((x - loc)/scale, dtype=dtyp)
zeta acceptanceProb 0 501 185 -789.0417578675533 2.2310189245534064 0.0
zeta acceptanceProb 0 504 185 -1002.0047705440686 2.456954246454124 0.0
/opt/anaconda2/lib/python2.7/site-packages/scipy/stats/_distn_infrastructure.py:1745: RuntimeWarning: divide by zero encountered in double_scalars
x = np.asarray((x - loc)/scale, dtype=dtyp)
/opt/anaconda2/lib/python2.7/site-packages/scipy/stats/_distn_infrastructure.py:1745: RuntimeWarning: divide by zero encountered in double_scalars
x = np.asarray((x - loc)/scale, dtype=dtyp)
/opt/anaconda2/lib/python2.7/site-packages/scipy/stats/_distn_infrastructure.py:1745: RuntimeWarning: divide by zero encountered in double_scalars
x = np.asarray((x - loc)/scale, dtype=dtyp)
zeta acceptanceProb 0 507 185 -2571.43632624309 4.200507463890091 0.0
zeta acceptanceProb 0 502 185 -1806.380340905146 4.732995592233772 0.0
zeta acceptanceProb 0 503 185 -1540.2331460700905 2.1958353500386116 0.0
zeta acceptanceProb 0 509 185 -2408.3827297097564 2.2170070598483087 0.0
zeta acceptanceProb 0 504 185 -1253.9332119216615 4.64564519578607 0.0
zeta acceptanceProb 0 505 185 -1476.483469410981 5.058926437999797 0.0
eta acceptanceProb 0 506 234 -774.9440382433543 4.322598751737026 0.0
zeta acceptanceProb 0 506 185 -1039.827147988062 5.323807772780286 0.0
zeta acceptanceProb 0 507 185 -1040.4778272527863 5.131095465952665 0.0
zeta acceptanceProb 0 514 185 -2793.6021110676065 2.1151658446296318 0.0
zeta acceptanceProb 0 515 32 -939.1208529007952 5.969761947757672 0.0
zeta acceptanceProb 0 510 185 -977.6687615177743 2.327868329046156 0.0
zeta acceptanceProb 0 512 185 -978.4254174930202 2.354707637495217 0.0
zeta acceptanceProb 0 517 185 -1104.1283827410846 2.318428295806438 0.0
zeta acceptanceProb 0 518 32 -823.9843750582321 3.167079970979633 0.0
zeta acceptanceProb 0 520 185 -1674.6336850715475 0.516207756458237 0.0
zeta acceptanceProb 0 520 32 -1007.4678954832227 6.472196637921657 0.0
zeta acceptanceProb 0 526 185 -1848.2450336175361 4.664913532817367 0.0
zeta acceptanceProb 0 528 185 -1364.5923147519757 4.596424717297591 0.0
zeta acceptanceProb 0 530 185 -2403.254399963869 3.722010938467012 0.0
zeta acceptanceProb 0 533 32 -953.869295237475 2.6549549406421034 0.0
zeta acceptanceProb 0 533 185 -823.6897827566747 4.268774489232163 0.0
zeta acceptanceProb 0 530 185 -1461.895684904956 2.7242533507374747 0.0
zeta acceptanceProb 0 530 185 -755.86699697113 2.5402226958364063 0.0
zeta acceptanceProb 0 536 32 -1112.5621159300492 6.363109692350125 0.0
zeta acceptanceProb 0 531 185 -813.846015039251 0.757082529487922 0.0
zeta acceptanceProb 0 537 185 -865.5981446147387 4.2423839127930565 0.0
zeta acceptanceProb 0 540 185 -1012.0625522018405 1.5425291308996574 0.0
zeta acceptanceProb 0 546 185 -890.3101349663921 5.131771113178749 0.0
zeta acceptanceProb 0 541 185 -2408.6910288388926 4.744258762737102 0.0
zeta acceptanceProb 0 542 185 -1052.5113462164366 4.570881219775883 0.0
zeta acceptanceProb 0 543 185 -1750.3262574399207 5.301650439218328 0.0
zeta acceptanceProb 0 544 185 -1808.5065469650099 5.145401262192676 0.0
zeta acceptanceProb 0 544 185 -982.8797383108815 4.7288447805751685 0.0
zeta acceptanceProb 0 545 185 -972.502381947574 4.956167639523686 0.0
zeta acceptanceProb 0 554 185 -2381.535548858051 3.7538317900110236 0.0
zeta acceptanceProb 0 549 185 -1222.675115012245 4.546383350111026 0.0
zeta acceptanceProb 0 553 185 -4407.543823654431 5.591621659460614 0.0
zeta acceptanceProb 0 554 185 -2170.8791477300106 5.591292109717065 0.0
zeta acceptanceProb 0 555 185 -1125.692245350196 3.0060917485376897 0.0
zeta acceptanceProb 0 560 185 -1009.0137073928252 4.116904295870306 0.0
zeta acceptanceProb 0 565 185 -875.2289751800902 3.542451053853663 0.0
zeta acceptanceProb 0 562 185 -1758.7809742723246 3.2884308460681053 0.0
zeta acceptanceProb 0 564 32 -1033.781839912879 6.6043648827022725 0.0
zeta acceptanceProb 0 564 185 -817.1335849069678 3.9192004758362318 0.0
zeta acceptanceProb 0 565 32 -1446.4341799965387 4.54755903833594 0.0
zeta acceptanceProb 0 571 185 -1075.9481639700616 5.081848295289081 0.0
zeta acceptanceProb 0 566 32 -1040.9496285022512 5.101181726132674 0.0
zeta acceptanceProb 0 567 32 -1058.0674529288087 3.5640027483443815 0.0
zeta acceptanceProb 0 572 185 -2572.362289683205 5.081848295289081 0.0
zeta acceptanceProb 0 568 32 -972.4288509602263 4.631801283774975 0.0
zeta acceptanceProb 0 568 185 -845.7032748989291 4.776075952579183 0.0
zeta acceptanceProb 0 575 185 -1627.1473113201487 4.289469779502392 0.0
zeta acceptanceProb 0 576 185 -1318.4228918466304 4.014449532045811 0.0
zeta acceptanceProb 0 578 185 -1228.799862190359 4.016881921181193 0.0
zeta acceptanceProb 0 573 185 -1116.5588156100428 0.5192578793388618 0.0
zeta acceptanceProb 0 579 185 -1335.7092046196335 4.486681872245142 0.0
zeta acceptanceProb 0 575 185 -1190.6558208617455 4.0632494873302605 0.0
zeta acceptanceProb 0 576 32 -990.4867774677617 5.380885992239997 0.0
zeta acceptanceProb 0 577 32 -1376.333698493589 3.989149596858258 0.0
zeta acceptanceProb 0 584 185 -2134.0585131231323 2.82091069592076 0.0
zeta acceptanceProb 0 583 185 -1650.5364429538954 4.667791423953371 0.0
zeta acceptanceProb 0 584 32 -1140.9238284319767 5.794333728660084 0.0
zeta acceptanceProb 0 585 185 -1768.5026890681 4.727029231171377 0.0
zeta acceptanceProb 0 586 32 -964.6333804066147 5.657668965044066 0.0
zeta acceptanceProb 0 587 185 -1215.1368485446246 4.726712922608742 0.0
zeta acceptanceProb 0 591 185 -1138.0260940733842 4.7197523956082925 0.0
zeta acceptanceProb 0 593 32 -1276.7571755876234 5.037957756746609 0.0
zeta acceptanceProb 0 593 185 -958.3443449282059 1.4571520170890953 0.0
zeta acceptanceProb 0 594 32 -3943.089500019186 4.901996877248503 0.0
zeta acceptanceProb 0 595 185 -756.5845977725154 3.334017919630025 0.0
zeta acceptanceProb 0 597 32 -953.3262309618723 4.910910755130021 0.0
zeta acceptanceProb 0 598 32 -1352.7780516506064 4.942807825906475 0.0
zeta acceptanceProb 0 599 32 -747.5893396977876 5.257056738302168 0.0
zeta acceptanceProb 0 600 32 -766.4680641968115 4.097931002710298 0.0
zeta acceptanceProb 0 602 185 -883.3668055438206 -1.4849966271041612 0.0
zeta acceptanceProb 0 608 185 -785.7949956925398 2.5971026980787526 0.0
zeta acceptanceProb 0 605 32 -1577.310930240199 4.257504802146211 0.0
zeta acceptanceProb 0 609 32 -794.5121448222135 6.186279546447723 0.0
zeta acceptanceProb 0 612 185 -763.7441444925269 0.4572168129535221 0.0
zeta acceptanceProb 0 613 185 -972.5372505673745 4.2070343136771085 0.0
zeta acceptanceProb 0 624 32 -847.1576451300043 6.4127903071546015 0.0
zeta acceptanceProb 0 624 185 -797.0437880219622 2.063616017168508 0.0
zeta acceptanceProb 0 629 185 -826.4523619175824 2.4106982422197927 0.0
zeta acceptanceProb 0 630 32 -1528.842489262027 6.280745425402779 0.0
zeta acceptanceProb 0 639 185 -784.5973404294735 3.353002918711302 0.0
zeta acceptanceProb 0 641 185 -1726.3998194431324 2.6028064391128547 0.0
zeta acceptanceProb 0 646 185 -1476.7214179774483 2.4347867476284595 0.0
zeta acceptanceProb 0 665 185 -922.2188725856124 4.6437429149918925 0.0
zeta acceptanceProb 0 662 185 -899.4815829814555 1.4193892154302619 0.0
zeta acceptanceProb 0 672 185 -955.0046877184006 3.172122194740612 0.0
zeta acceptanceProb 0 678 185 -1066.882883092738 4.214916299860682 0.0
zeta acceptanceProb 0 680 185 -1012.3288355246384 4.69643655502502 0.0
zeta acceptanceProb 0 683 185 -1923.7203138310122 3.6026035209035085 0.0
zeta acceptanceProb 0 682 32 -1636.9816648313138 6.597847685651999 0.0
zeta acceptanceProb 0 683 185 -1351.0204599651306 1.646583046350833 0.0
zeta acceptanceProb 0 688 185 -943.5639673406888 2.252048730346122 0.0
zeta acceptanceProb 0 689 185 -774.7826228232929 0.5851155653312423 0.0
zeta acceptanceProb 0 692 185 -1060.0020060529928 2.2822584886633126 0.0
zeta acceptanceProb 0 696 185 -824.2948961193496 4.232626853671194 0.0
zeta acceptanceProb 0 697 185 -886.3043106328893 3.699803222769506 0.0
zeta acceptanceProb 0 699 185 -1902.849169273489 4.446963423998676 0.0
zeta acceptanceProb 0 700 32 -1440.0333102855934 5.528400400855199 0.0
zeta acceptanceProb 0 712 185 -895.1424238511717 3.937278546844943 0.0
zeta acceptanceProb 0 760 32 -786.0173509559734 5.851089091121496 0.0
zeta acceptanceProb 0 764 32 -778.0430995559839 6.103070983638454 0.0
zeta acceptanceProb 0 779 185 -1198.9874091927693 5.033053685077258 0.0
zeta acceptanceProb 0 793 185 -934.6501239652454 3.0126417064556463 0.0
zeta acceptanceProb 0 810 32 -1561.1583823791514 6.021369985191816 0.0
zeta acceptanceProb 0 818 185 -758.631258510848 4.255669420838839 0.0
zeta acceptanceProb 0 843 185 -1017.4833223710637 0.18148916559715822 0.0
zeta acceptanceProb 0 844 32 -1279.682017347815 5.950871506851275 0.0
zeta acceptanceProb 0 878 32 -974.6799790918373 6.54716109850518 0.0
zeta acceptanceProb 0 886 32 -931.7096391568017 4.286612360803592 0.0
eta acceptanceProb 0 930 260 -1435.2127573138803 2.2697733772901802 0.0
1000
1000
1000
1000
Traceback (most recent call last):
File "/opt/anaconda2/lib/python2.7/site-packages/IPython/core/formatters.py", line 334, in __call__
return printer(obj)
File "/opt/anaconda2/lib/python2.7/site-packages/IPython/core/pylabtools.py", line 247, in <lambda>
png_formatter.for_type(Figure, lambda fig: print_figure(fig, 'png', **kwargs))
File "/opt/anaconda2/lib/python2.7/site-packages/IPython/core/pylabtools.py", line 131, in print_figure
fig.canvas.print_figure(bytes_io, **kw)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/backend_bases.py", line 2212, in print_figure
**kwargs)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/backends/backend_agg.py", line 517, in print_png
FigureCanvasAgg.draw(self)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/backends/backend_agg.py", line 437, in draw
self.figure.draw(self.renderer)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/artist.py", line 55, in draw_wrapper
return draw(artist, renderer, *args, **kwargs)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/figure.py", line 1493, in draw
renderer, self, artists, self.suppressComposite)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/image.py", line 141, in _draw_list_compositing_images
a.draw(renderer)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/artist.py", line 55, in draw_wrapper
return draw(artist, renderer, *args, **kwargs)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/axes/_base.py", line 2635, in draw
mimage._draw_list_compositing_images(renderer, self, artists)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/image.py", line 141, in _draw_list_compositing_images
a.draw(renderer)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/artist.py", line 55, in draw_wrapper
return draw(artist, renderer, *args, **kwargs)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/legend.py", line 775, in draw
bbox = self._legend_box.get_window_extent(renderer)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/offsetbox.py", line 266, in get_window_extent
w, h, xd, yd, offsets = self.get_extent_offsets(renderer)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/offsetbox.py", line 388, in get_extent_offsets
for c in self.get_visible_children()]
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/offsetbox.py", line 259, in get_extent
w, h, xd, yd, offsets = self.get_extent_offsets(renderer)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/offsetbox.py", line 458, in get_extent_offsets
for c in self.get_visible_children()]
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/offsetbox.py", line 259, in get_extent
w, h, xd, yd, offsets = self.get_extent_offsets(renderer)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/offsetbox.py", line 388, in get_extent_offsets
for c in self.get_visible_children()]
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/offsetbox.py", line 259, in get_extent
w, h, xd, yd, offsets = self.get_extent_offsets(renderer)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/offsetbox.py", line 458, in get_extent_offsets
for c in self.get_visible_children()]
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/offsetbox.py", line 831, in get_extent
bbox, info, d = self._text._get_layout(renderer)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/text.py", line 309, in _get_layout
ismath=ismath)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/backends/backend_agg.py", line 236, in get_text_width_height_descent
s, fontsize, renderer=self)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/texmanager.py", line 501, in get_text_width_height_descent
dvifile = self.make_dvi(tex, fontsize)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/texmanager.py", line 362, in make_dvi
with Locked(self.texcache):
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/cbook/__init__.py", line 2529, in __enter__
raise self.TimeoutError(err_str)
TimeoutError: LOCKERROR: matplotlib is trying to acquire the lock
'/Users/lester/.matplotlib/tex.cache/.matplotlib_lock-*'
and has failed. This maybe due to any other process holding this
lock. If you are sure no other matplotlib process is running try
removing these folders and trying again.
<Figure size 576x576 with 4 Axes>
Traceback (most recent call last):
File "/opt/anaconda2/lib/python2.7/site-packages/IPython/core/formatters.py", line 334, in __call__
return printer(obj)
File "/opt/anaconda2/lib/python2.7/site-packages/IPython/core/pylabtools.py", line 247, in <lambda>
png_formatter.for_type(Figure, lambda fig: print_figure(fig, 'png', **kwargs))
File "/opt/anaconda2/lib/python2.7/site-packages/IPython/core/pylabtools.py", line 131, in print_figure
fig.canvas.print_figure(bytes_io, **kw)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/backend_bases.py", line 2212, in print_figure
**kwargs)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/backends/backend_agg.py", line 517, in print_png
FigureCanvasAgg.draw(self)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/backends/backend_agg.py", line 437, in draw
self.figure.draw(self.renderer)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/artist.py", line 55, in draw_wrapper
return draw(artist, renderer, *args, **kwargs)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/figure.py", line 1493, in draw
renderer, self, artists, self.suppressComposite)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/image.py", line 141, in _draw_list_compositing_images
a.draw(renderer)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/artist.py", line 55, in draw_wrapper
return draw(artist, renderer, *args, **kwargs)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/axes/_base.py", line 2635, in draw
mimage._draw_list_compositing_images(renderer, self, artists)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/image.py", line 141, in _draw_list_compositing_images
a.draw(renderer)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/artist.py", line 55, in draw_wrapper
return draw(artist, renderer, *args, **kwargs)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/legend.py", line 775, in draw
bbox = self._legend_box.get_window_extent(renderer)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/offsetbox.py", line 266, in get_window_extent
w, h, xd, yd, offsets = self.get_extent_offsets(renderer)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/offsetbox.py", line 388, in get_extent_offsets
for c in self.get_visible_children()]
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/offsetbox.py", line 259, in get_extent
w, h, xd, yd, offsets = self.get_extent_offsets(renderer)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/offsetbox.py", line 458, in get_extent_offsets
for c in self.get_visible_children()]
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/offsetbox.py", line 259, in get_extent
w, h, xd, yd, offsets = self.get_extent_offsets(renderer)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/offsetbox.py", line 388, in get_extent_offsets
for c in self.get_visible_children()]
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/offsetbox.py", line 259, in get_extent
w, h, xd, yd, offsets = self.get_extent_offsets(renderer)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/offsetbox.py", line 458, in get_extent_offsets
for c in self.get_visible_children()]
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/offsetbox.py", line 831, in get_extent
bbox, info, d = self._text._get_layout(renderer)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/text.py", line 309, in _get_layout
ismath=ismath)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/backends/backend_agg.py", line 236, in get_text_width_height_descent
s, fontsize, renderer=self)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/texmanager.py", line 501, in get_text_width_height_descent
dvifile = self.make_dvi(tex, fontsize)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/texmanager.py", line 362, in make_dvi
with Locked(self.texcache):
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/cbook/__init__.py", line 2529, in __enter__
raise self.TimeoutError(err_str)
TimeoutError: LOCKERROR: matplotlib is trying to acquire the lock
'/Users/lester/.matplotlib/tex.cache/.matplotlib_lock-*'
and has failed. This maybe due to any other process holding this
lock. If you are sure no other matplotlib process is running try
removing these folders and trying again.
<Figure size 576x576 with 4 Axes>
zeta acceptanceProb 0 1032 32 -1489.8976544289017 6.497278115037871 0.0
zeta acceptanceProb 0 1067 32 -1247.7946063912045 6.091520108039147 0.0
zeta acceptanceProb 0 1064 61 -761.6187619381487 4.608963869615923 0.0
zeta acceptanceProb 0 1187 61 -815.0766480381847 4.858873474866984 0.0
zeta acceptanceProb 0 1391 234 -961.1512937589661 4.813640034147037 0.0
1500 15000
1500 15000
1500
1500
1500 15000
1500
1500 15000
1500
Traceback (most recent call last):
File "/opt/anaconda2/lib/python2.7/site-packages/IPython/core/formatters.py", line 334, in __call__
return printer(obj)
File "/opt/anaconda2/lib/python2.7/site-packages/IPython/core/pylabtools.py", line 247, in <lambda>
png_formatter.for_type(Figure, lambda fig: print_figure(fig, 'png', **kwargs))
File "/opt/anaconda2/lib/python2.7/site-packages/IPython/core/pylabtools.py", line 131, in print_figure
fig.canvas.print_figure(bytes_io, **kw)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/backend_bases.py", line 2212, in print_figure
**kwargs)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/backends/backend_agg.py", line 517, in print_png
FigureCanvasAgg.draw(self)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/backends/backend_agg.py", line 437, in draw
self.figure.draw(self.renderer)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/artist.py", line 55, in draw_wrapper
return draw(artist, renderer, *args, **kwargs)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/figure.py", line 1493, in draw
renderer, self, artists, self.suppressComposite)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/image.py", line 141, in _draw_list_compositing_images
a.draw(renderer)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/artist.py", line 55, in draw_wrapper
return draw(artist, renderer, *args, **kwargs)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/axes/_base.py", line 2635, in draw
mimage._draw_list_compositing_images(renderer, self, artists)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/image.py", line 141, in _draw_list_compositing_images
a.draw(renderer)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/artist.py", line 55, in draw_wrapper
return draw(artist, renderer, *args, **kwargs)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/legend.py", line 775, in draw
bbox = self._legend_box.get_window_extent(renderer)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/offsetbox.py", line 266, in get_window_extent
w, h, xd, yd, offsets = self.get_extent_offsets(renderer)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/offsetbox.py", line 388, in get_extent_offsets
for c in self.get_visible_children()]
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/offsetbox.py", line 259, in get_extent
w, h, xd, yd, offsets = self.get_extent_offsets(renderer)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/offsetbox.py", line 458, in get_extent_offsets
for c in self.get_visible_children()]
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/offsetbox.py", line 259, in get_extent
w, h, xd, yd, offsets = self.get_extent_offsets(renderer)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/offsetbox.py", line 388, in get_extent_offsets
for c in self.get_visible_children()]
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/offsetbox.py", line 259, in get_extent
w, h, xd, yd, offsets = self.get_extent_offsets(renderer)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/offsetbox.py", line 458, in get_extent_offsets
for c in self.get_visible_children()]
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/offsetbox.py", line 831, in get_extent
bbox, info, d = self._text._get_layout(renderer)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/text.py", line 309, in _get_layout
ismath=ismath)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/backends/backend_agg.py", line 236, in get_text_width_height_descent
s, fontsize, renderer=self)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/texmanager.py", line 501, in get_text_width_height_descent
dvifile = self.make_dvi(tex, fontsize)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/texmanager.py", line 362, in make_dvi
with Locked(self.texcache):
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/cbook/__init__.py", line 2529, in __enter__
raise self.TimeoutError(err_str)
TimeoutError: LOCKERROR: matplotlib is trying to acquire the lock
'/Users/lester/.matplotlib/tex.cache/.matplotlib_lock-*'
and has failed. This maybe due to any other process holding this
lock. If you are sure no other matplotlib process is running try
removing these folders and trying again.
<Figure size 576x576 with 4 Axes>
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.794594798871781 0.0 0.0 1.5777214931061376 0.0 0.0 0.460642522872 1.0 0.500851625086 0.26598040842 0.59278163323 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.5696166942790002 0.0 0.0 1.4493933228458638 0.0 0.0 0.590020665671 1.0 0.504145892628 0.224777403797 0.340647914907 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.52495411129563 0.0 0.0 1.3106196125190275 0.0 0.0 0.402814098154 1.0 0.510667419452 0.469696718781 0.562391540526 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
xi acceptanceProb 0 1670 73 -4130.288308783125 0.6687159905319516 0.0
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.5866557818967606 0.0 0.0 1.4121894452689547 0.0 0.0 0.477448087025 1.0 0.543062891989 0.387605193255 0.510014908636 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.6948950952550892 0.0 0.0 1.535616856215451 0.0 0.0 0.461158461364 1.0 0.56125929322 0.387605193255 0.510014908636 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.6948950952550892 0.0 0.0 1.535616856215451 0.0 0.0 0.461158461364 1.0 0.520184944088 0.428127223892 0.403912963307 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.7898797352021332 0.0 0.0 1.656541478328576 0.0 0.0 0.400544849076 1.0 0.51083844761 0.509310589398 0.516983575128 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.7898797352021332 0.0 0.0 1.656541478328576 0.0 0.0 0.383584547139 1.0 0.510171477143 0.509310589398 0.516983575128 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.7898797352021332 0.0 0.0 1.656541478328576 0.0 0.0 0.383584547139 1.0 0.507213899036 0.417775877054 0.516983575128 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.9174950867969935 0.0 0.0 1.7138556321914051 0.0 0.0 0.383584547139 1.0 0.536859512658 0.28768451662 0.516983575128 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 2.045742444966012 0.0 0.0 1.9335976971341002 0.0 0.0 0.410169312147 1.0 0.51165004908 0.519035809734 0.485690818232 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
2000
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.8358124037509702 0.0 0.0 1.8105494005448943 0.0 0.0 0.37152636559 1.0 0.508598704461 0.519035809734 0.485690818232 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
2000
2000
2000
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.7003106017917778 0.0 0.0 0.8129557858763222 0.0 0.0 0.168236524126 1.0 0.512357721976 0.885158846678 0.799133323229 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.7329297605948479 0.0 0.0 0.8324102467463915 0.0 0.0 0.109532781379 1.0 0.555938956997 0.90312904132 0.746232023896 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.6570268999270948 0.0 0.0 0.7988500174789982 0.0 0.0 0.153405369639 1.0 0.503701370796 0.833937413878 0.875660857088 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.380140361202328 0.0 0.0 1.1897058480195748 0.0 0.0 0.605195238937 1.0 0.516315478882 0.12368373621 0.457020269335 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
zeta acceptanceProb 0 2155 172 -834.7357741936838 -4.716049350985279 0.0
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.8111130429271733 0.0 0.0 0.8775228518631822 0.0 0.0 0.210236800624 1.0 0.631403660417 0.788066439545 0.911187911686 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
zeta acceptanceProb 0 2209 172 -2094.66021880612 -1.6000460912020082 0.0
zeta acceptanceProb 0 2218 172 -963.2778512666496 -0.887145119724098 0.0
eta acceptanceProb 0 2246 95 -1082.2752166141447 2.585157560078272 0.0
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.7883983626660187 0.0 0.0 0.8236427067995289 0.0 0.0 0.180765684845 1.0 0.551540816084 0.866161302902 0.79678953037 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.7156878534493253 0.0 0.0 0.7510617788356095 0.0 0.0 0.142851082876 1.0 0.513070269231 0.882839673659 0.940056483926 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.9530131874597386 0.0 0.0 0.906296775153212 0.0 0.0 0.28987229835 1.0 0.510312591038 0.722894602923 1.14067786431 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
eta acceptanceProb 0 2358 72 -757.0918582945492 3.647215039350252 0.0
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.0106488972837335 0.0 0.0 1.065317958128593 0.0 0.0 0.235590487204 1.0 0.529615321476 0.602614007504 0.793476966338 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
zeta acceptanceProb 0 2474 172 -799.8069077921383 0.3430323745029114 0.0
zeta acceptanceProb 0 2479 172 -902.372526395665 0.2786788213425914 0.0
zeta acceptanceProb 0 2487 172 -874.8307015042591 -2.444772032082322 0.0
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.709053821352737 0.0 0.0 0.8068917436493931 0.0 0.0 0.104512716338 1.0 0.553001109587 0.944497358051 0.906411064613 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
zeta acceptanceProb 0 2489 172 -1031.4562281603828 -1.3091966480389932 0.0
zeta acceptanceProb 0 2491 172 -1304.5724160617217 -1.1225249606165284 0.0
2500
zeta acceptanceProb 0 2497 172 -826.8454945327326 -0.9390742488514787 0.0
2500
2500
2500
zeta acceptanceProb 0 2506 172 -787.5371044460389 -0.6339510720359782 0.0
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.0529874946447442 0.0 0.0 1.0473582590825594 0.0 0.0 0.311098806518 1.0 0.532185819991 1.1376994589 0.734549318531 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
zeta acceptanceProb 0 2564 172 -929.0034341857037 -4.555917300092382 0.0
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.7212222017332749 0.0 0.0 0.7478777466563784 0.0 0.0 0.174657556857 1.0 0.525088915498 1.52504173155 0.866619905655 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
xi acceptanceProb 0 2569 211 -2064.170185865909 -1.01757073719298 0.0
zeta acceptanceProb 0 2569 211 -5742.944768730726 3.492797062983407 0.0
zeta acceptanceProb 0 2570 211 -24505.235000673187 3.045372461965569 0.0
zeta acceptanceProb 0 2573 172 -777.8408964995125 0.2536507334650428 0.0
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.7713843234436414 0.0 0.0 0.7675209635603422 0.0 0.0 0.167678470297 1.0 0.509430307988 0.9546717815 0.813891035295 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
zeta acceptanceProb 0 2612 172 -974.3458586314487 -1.1837402236606984 0.0
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.1650201294962546 0.0 0.0 1.1414925611436937 0.0 0.0 0.318223460941 1.0 0.570316315547 1.21312625964 0.900991013455 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
zeta acceptanceProb 0 2638 172 -1066.3112631886524 -0.2086163901312128 0.0
zeta acceptanceProb 0 2668 172 -863.5047603308831 -0.4184419831909113 0.0
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.0702196589894513 0.0 0.0 0.9532739313270439 0.0 0.0 0.371231588591 1.0 0.512955448042 0.926658990008 0.970234534062 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
3000 15000
3000
3000 15000
3000
3000 15000
3000
3000 15000
3000
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.136201267183638 0.0 0.0 1.1107604678654883 0.0 0.0 0.275580341429 1.0 0.56393636448 1.10301628281 0.882966990766 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.9131109769480203 0.0 0.0 0.9688604705483049 0.0 0.0 0.192825136242 1.0 0.567772959969 0.727933253588 0.789138127757 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.9065183188330459 0.0 0.0 0.9841631501766906 0.0 0.0 0.190968019357 1.0 0.541068518385 0.867229386035 0.904488728279 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.8671478713757834 0.0 0.0 0.9472348467953675 0.0 0.0 0.210056384817 1.0 0.525093315494 0.777581490693 0.830536274185 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.9205596428372445 0.0 0.0 0.9751477387001919 0.0 0.0 0.220511653529 1.0 0.530026129125 0.68567434373 0.85280199528 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.9205596428372445 0.0 0.0 0.9751477387001919 0.0 0.0 0.221720329367 1.0 0.615787683871 0.68567434373 0.85280199528 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
eta acceptanceProb 0 3153 260 -1022.3225446450662 -0.02040818252172638 0.0
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.8531271701245591 0.0 0.0 0.9072823956029079 0.0 0.0 0.199043075014 1.0 0.723910655436 0.893226364255 0.873480341554 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.9487241913375052 0.0 0.0 1.0060840776817548 0.0 0.0 0.200300325895 1.0 0.533240659335 1.10606087892 0.908856952016 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
eta acceptanceProb 0 3175 72 -756.3403530909422 -0.23289973768309924 0.0
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.0088787791938396 0.0 0.0 1.0294828249391281 0.0 0.0 0.239877338338 1.0 0.549273481579 0.695485437791 0.997850292127 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
xi acceptanceProb 0 3200 73 -28054.14000736551 2.2470011009160538 0.0
zeta acceptanceProb 0 3200 73 -1300.4849085983783 3.3805932282979256 0.0
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.015727705098762 0.0 0.0 1.0204962489939704 0.0 0.0 0.244893901991 1.0 0.532036121702 0.787727674517 0.832241712447 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.1525978551808203 0.0 0.0 1.2039834764633204 0.0 0.0 0.246818421505 1.0 0.564794788076 0.71558812301 0.89892709442 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.1926589173214823 0.0 0.0 1.2361760595182065 0.0 0.0 0.243696615174 1.0 0.543834325999 0.71558812301 0.846978129525 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.1748357369502114 0.0 0.0 1.2041982461864822 0.0 0.0 0.232220069574 1.0 0.538935473664 1.06144182595 0.768839854978 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.0856831261775797 0.0 0.0 1.1116262875214797 0.0 0.0 0.320224602145 1.0 0.540365621741 0.84962922413 0.986654141022 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
3500
3500
3500
3500
xi acceptanceProb 0 3539 73 -63681.50542975427 3.0832277862064124 0.0
zeta acceptanceProb 0 3539 73 -749.817452172107 3.172257826491071 0.0
zeta acceptanceProb 0 3658 211 -3033.7144334644595 3.269892293665933 0.0
xi acceptanceProb 0 3659 211 -1570.4574613004154 2.998340499040532 0.0
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.0862055726164717 0.0 0.0 1.0705533998030887 0.0 0.0 0.309991069507 1.0 0.540315611224 0.962442942551 0.767338381811 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.0277972428923776 0.0 0.0 0.9357431022055842 0.0 0.0 0.301433217338 1.0 0.537713655073 0.763339626028 0.946003226167 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.2022904961087253 0.0 0.0 1.1945435909588173 0.0 0.0 0.271348792011 1.0 0.556100961654 1.0438268692 0.88672738914 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.1354194901707169 0.0 0.0 1.1377442480507212 0.0 0.0 0.250691253724 1.0 0.519768686015 0.879148618926 0.882990348428 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.2248098376800824 0.0 0.0 1.242859604788664 0.0 0.0 0.226495932271 1.0 0.520081324558 0.896509325056 0.782479776715 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.159213997591466 0.0 0.0 1.1407294278507414 0.0 0.0 0.245193212366 1.0 0.510795986391 0.792659367289 0.819907050263 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.1954512938704853 0.0 0.0 1.157291892724901 0.0 0.0 0.223623752732 1.0 0.513199865092 0.833596212374 0.899677790141 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.0737100782063624 0.0 0.0 0.9437515630865199 0.0 0.0 0.323586256435 1.0 0.587490389248 1.14018570245 0.939038489139 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.0913359067523667 0.0 0.0 0.9672467228381636 0.0 0.0 0.306452238903 1.0 0.505047020473 0.965159842356 0.968927711846 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.9116393842463392 0.0 0.0 0.9941437674385097 0.0 0.0 0.195829059579 1.0 0.539059859849 0.784506142536 0.711663169157 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
4000
4000
4000
4000
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.1428792672692165 0.0 0.0 1.058354742561847 0.0 0.0 0.282615105098 1.0 0.527676736656 0.807593032747 0.871735453038 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.172960105140604 0.0 0.0 1.161077091608122 0.0 0.0 0.319755824645 1.0 0.506113643679 1.08347247389 0.864188753506 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
xi acceptanceProb 0 4097 73 -59574.990055137634 3.5201141975900803 0.0
zeta acceptanceProb 0 4097 73 -8687.141368624738 3.4690657973400922 0.0
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.9281061172469636 0.0 0.0 0.899716227758325 0.0 0.0 0.279233661904 1.0 0.574568044938 0.836490991584 1.06049027198 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.8709467204946167 0.0 0.0 0.9279335658952805 0.0 0.0 0.234071169655 1.0 0.549055883125 0.967697996552 0.954703877996 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.0223834712072644 0.0 0.0 1.0493679960645512 0.0 0.0 0.19937989742 1.0 0.548363833507 0.849328125137 0.925063486594 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.0175151931820654 0.0 0.0 1.027275374635377 0.0 0.0 0.2824289186 1.0 0.574187484338 1.08598864265 0.83759291129 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.9909304756751599 0.0 0.0 1.0034300503911913 0.0 0.0 0.279896091335 1.0 0.59851667568 0.743216923597 0.827503101904 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.8376323208341505 0.0 0.0 0.8447199892357931 0.0 0.0 0.181201553053 1.0 0.518439812468 0.70911297334 0.790239447307 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.7612520566876436 0.0 0.0 0.7806361685262625 0.0 0.0 0.16916861021 1.0 0.501685781598 0.807583637938 1.0245390161 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.0465717506706476 0.0 0.0 1.0518264226875824 0.0 0.0 0.256938991376 1.0 0.510820788468 1.08839727391 0.994078943311 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.1312250814708136 0.0 0.0 1.1621740724145393 0.0 0.0 0.284719721287 1.0 0.500838355314 0.99811176147 0.882097980488 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.0640985086739785 0.0 0.0 1.117461730570291 0.0 0.0 0.348756760091 1.0 0.536913073775 0.774445780539 0.675305843363 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
zeta acceptanceProb 0 4381 248 -922.2871044958234 1.5942904654617835 0.0
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.042590165236429 0.0 0.0 1.0794243513970183 0.0 0.0 0.376216322989 1.0 0.514595462088 0.816190890935 0.906087570539 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
4500 15000
4500
4500 15000
4500
4500 15000
4500
4500 15000
4500
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.0213442122555483 0.0 0.0 0.9796305505702649 0.0 0.0 0.289092972904 1.0 0.516572715513 1.38525570587 0.947698431445 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
zeta acceptanceProb 0 4680 211 -3143.4122315054674 6.700607274667562 0.0
zeta acceptanceProb 0 4681 211 -23732.75925964529 6.703556097778439 0.0
zeta acceptanceProb 0 4682 211 -13275.48167452627 6.664364772567335 0.0
xi acceptanceProb 0 4683 211 -22994.931187721242 6.481778327790524 0.0
zeta acceptanceProb 0 4683 211 -6065.0009742597 6.664364772567335 0.0
xi acceptanceProb 0 4684 211 -2538.985156036406 6.5828110353096285 0.0
zeta acceptanceProb 0 4684 211 -10284.619824696894 6.685039781744975 0.0
xi acceptanceProb 0 4685 211 -945.2117080275735 6.5543719560450056 0.0
zeta acceptanceProb 0 4685 211 -1316.714285444431 6.774298860662539 0.0
xi acceptanceProb 0 4686 211 -846.6115712086737 6.576886597347126 0.0
zeta acceptanceProb 0 4687 211 -1403.1160295260102 6.735646715759986 0.0
xi acceptanceProb 0 4688 211 -11459.3006298651 6.387329995246704 0.0
xi acceptanceProb 0 4689 211 -3688.153018955835 6.338096853446365 0.0
zeta acceptanceProb 0 4689 211 -4176.280432408575 6.756990626915719 0.0
xi acceptanceProb 0 4690 211 -3915.711560446165 6.320745079709903 0.0
zeta acceptanceProb 0 4691 211 -11079.706043178992 6.7791381359542395 0.0
zeta acceptanceProb 0 4692 211 -31475.459841652555 6.7292163869169555 0.0
xi acceptanceProb 0 4693 211 -4091.255626873887 6.020938819625895 0.0
zeta acceptanceProb 0 4694 211 -3000.009162974322 6.7387581211380025 0.0
zeta acceptanceProb 0 4695 211 -4553.488424114522 6.737864354448997 0.0
xi acceptanceProb 0 4696 211 -2567.4154123436806 6.0942402301009535 0.0
xi acceptanceProb 0 4697 211 -850.7499193810721 6.111586766242111 0.0
zeta acceptanceProb 0 4697 211 -8969.48911966094 6.812623797082334 0.0
xi acceptanceProb 0 4698 211 -4308.706108119434 6.18782372426015 0.0
zeta acceptanceProb 0 4698 211 -69820.05571914547 6.050432078529487 0.0
zeta acceptanceProb 0 4699 211 -32925.739349234515 6.041929379150647 0.0
zeta acceptanceProb 0 4700 211 -27837.313361706194 6.019498986528329 0.0
xi acceptanceProb 0 4701 211 -1421.8031765393132 6.7916334330493715 0.0
zeta acceptanceProb 0 4701 211 -2720.4356040854377 -1.233033738295146 0.0
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.9697890241523612 0.0 0.0 0.917531352429455 0.0 0.0 0.312310494024 1.0 0.540453384934 1.19436411769 0.842496377039 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.9182171931064765 0.0 0.0 1.009193864796955 0.0 0.0 0.249795116116 1.0 0.532336645076 0.831778670321 0.814062579315 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.9182171931064765 0.0 0.0 1.009193864796955 0.0 0.0 0.287893205147 1.0 0.500753875323 0.927724123211 0.762772442009 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.9182171931064765 0.0 0.0 1.009193864796955 0.0 0.0 0.260183051827 1.0 0.528416638274 0.757895092281 0.782332262826 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.9370911385646796 0.0 0.0 1.0660033715686537 0.0 0.0 0.252420570339 1.0 0.550472229238 0.962866401474 0.694786360065 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.0807937135246617 0.0 0.0 1.1955313245476937 0.0 0.0 0.236226609384 1.0 0.536936551503 0.611329271441 0.919490185846 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.0807937135246617 0.0 0.0 1.1955313245476937 0.0 0.0 0.236226609384 1.0 0.503394897333 0.542710169783 0.947305679756 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.0807937135246617 0.0 0.0 1.1955313245476937 0.0 0.0 0.243615659072 1.0 0.516290073504 0.691893533153 0.947305679756 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
zeta acceptanceProb 0 4896 211 -9286.621635098389 0.7958460417750173 0.0
5000
5000
5000
5000
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.142599365000258 0.0 0.0 1.103848294918769 0.0 0.0 0.207458858132 1.0 0.52328842439 0.916278845144 0.773257902992 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.183006610213876 0.0 0.0 1.1787127719314807 0.0 0.0 0.205912786254 1.0 0.550506426074 0.897774346932 0.881567306735 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
eta acceptanceProb 0 5202 260 -1569.373507030836 3.6277400659714987 0.0
eta acceptanceProb 0 5203 260 -821.436146835637 3.6135790512271297 0.0
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.159668871881797 0.0 0.0 1.0934118912135444 0.0 0.0 0.257255224375 1.0 0.53067555303 0.630463018466 0.999124633864 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.1071276282078146 0.0 0.0 1.0221057634185722 0.0 0.0 0.268711064733 1.0 0.528913671635 1.00492982813 0.792433035214 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.1071276282078146 0.0 0.0 1.0221057634185722 0.0 0.0 0.240588522853 1.0 0.524671021666 0.942896760415 0.792433035214 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.9109564670227277 0.0 0.0 0.9064597029441281 0.0 0.0 0.232622469732 1.0 0.501778353474 0.93318145744 0.900166485194 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
zeta acceptanceProb 0 5228 248 -746.6069459091523 1.3110148629613843 0.0
xi acceptanceProb 0 5240 73 -134986.44428973735 0.6788903157075908 0.0
zeta acceptanceProb 0 5240 73 -2700.5650352521434 1.3087571382124992 0.0
zeta acceptanceProb 0 5283 248 -871.1699457624386 1.571865973780426 0.0
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.8358293326127866 0.0 0.0 0.8528471404110428 0.0 0.0 0.276476211214 1.0 0.509410144563 1.00738325046 0.700279990662 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
zeta acceptanceProb 0 5365 172 -841.8811152957743 -1.3848441353743437 0.0
zeta acceptanceProb 0 5366 172 -1363.663534858995 -1.3843290781166337 0.0
zeta acceptanceProb 0 5370 172 -2203.201203040138 0.07622059429085767 0.0
zeta acceptanceProb 0 5375 172 -1484.295112658749 -0.47303604055734905 0.0
zeta acceptanceProb 0 5381 172 -3369.413195841104 -2.290007358466484 0.0
zeta acceptanceProb 0 5386 172 -934.78047598877 0.04964620582409479 0.0
zeta acceptanceProb 0 5392 172 -1755.7380512686216 -1.874746701614762 0.0
zeta acceptanceProb 0 5396 172 -1366.6930850473848 -0.8618532918378425 0.0
zeta acceptanceProb 0 5416 172 -2309.6410232465782 -3.9002280161054914 0.0
zeta acceptanceProb 0 5426 172 -927.2584238411664 -3.456807500842719 0.0
zeta acceptanceProb 0 5434 172 -875.8476839136429 -1.857775438478194 0.0
zeta acceptanceProb 0 5480 172 -1597.3681338154868 -1.1363652365754269 0.0
zeta acceptanceProb 0 5481 172 -893.8292937795939 -0.8998222656656251 0.0
zeta acceptanceProb 0 5483 172 -1754.5038800525087 -0.6585403053733967 0.0
5500
5500
zeta acceptanceProb 0 5500 172 -768.7065736386892 0.11739847780288376 0.0
5500
5500
zeta acceptanceProb 0 5506 172 -760.2233432001656 -1.9263639269482302 0.0
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.8041720856695823 0.0 0.0 0.8716749668123188 0.0 0.0 0.137456590972 1.0 0.535371839714 1.2185071603 0.842062683563 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
zeta acceptanceProb 0 5511 172 -820.2574161886447 0.7187217322720594 0.0
eta acceptanceProb 0 5548 72 -952.0016081650917 1.7204488458889586 0.0
zeta acceptanceProb 0 5553 172 -1288.2042353638676 0.5257918573985046 0.0
eta acceptanceProb 0 5594 72 -790.7718067818823 1.80000252048409 0.0
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.8907894501059804 0.0 0.0 1.0311844896283269 0.0 0.0 0.143858403074 1.0 0.502315235869 1.14830186935 0.824380228026 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.8907894501059804 0.0 0.0 1.0311844896283269 0.0 0.0 0.148716110853 1.0 0.512404446152 1.14830186935 0.824380228026 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.8847852490182763 0.0 0.0 1.0456466098504804 0.0 0.0 0.176863716461 1.0 0.543160883934 0.991181389209 0.880147782193 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
zeta acceptanceProb 0 5724 172 -1079.3713642262132 0.29683191728126757 0.0
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.8435815175108542 0.0 0.0 0.9216705248199071 0.0 0.0 0.137977721525 1.0 0.545611740332 0.939530877955 0.808354623169 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.8138174525221205 0.0 0.0 0.9083279021928498 0.0 0.0 0.195927081626 1.0 0.531402152957 1.21356268883 0.957515529106 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
6000 15000
6000
6000 15000
6000
6000 15000
6000
6000 15000
6000
Traceback (most recent call last):
File "/opt/anaconda2/lib/python2.7/site-packages/IPython/core/formatters.py", line 334, in __call__
return printer(obj)
File "/opt/anaconda2/lib/python2.7/site-packages/IPython/core/pylabtools.py", line 247, in <lambda>
png_formatter.for_type(Figure, lambda fig: print_figure(fig, 'png', **kwargs))
File "/opt/anaconda2/lib/python2.7/site-packages/IPython/core/pylabtools.py", line 131, in print_figure
fig.canvas.print_figure(bytes_io, **kw)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/backend_bases.py", line 2212, in print_figure
**kwargs)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/backends/backend_agg.py", line 517, in print_png
FigureCanvasAgg.draw(self)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/backends/backend_agg.py", line 437, in draw
self.figure.draw(self.renderer)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/artist.py", line 55, in draw_wrapper
return draw(artist, renderer, *args, **kwargs)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/figure.py", line 1493, in draw
renderer, self, artists, self.suppressComposite)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/image.py", line 141, in _draw_list_compositing_images
a.draw(renderer)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/artist.py", line 55, in draw_wrapper
return draw(artist, renderer, *args, **kwargs)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/axes/_base.py", line 2635, in draw
mimage._draw_list_compositing_images(renderer, self, artists)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/image.py", line 141, in _draw_list_compositing_images
a.draw(renderer)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/artist.py", line 55, in draw_wrapper
return draw(artist, renderer, *args, **kwargs)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/legend.py", line 775, in draw
bbox = self._legend_box.get_window_extent(renderer)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/offsetbox.py", line 266, in get_window_extent
w, h, xd, yd, offsets = self.get_extent_offsets(renderer)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/offsetbox.py", line 388, in get_extent_offsets
for c in self.get_visible_children()]
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/offsetbox.py", line 259, in get_extent
w, h, xd, yd, offsets = self.get_extent_offsets(renderer)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/offsetbox.py", line 458, in get_extent_offsets
for c in self.get_visible_children()]
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/offsetbox.py", line 259, in get_extent
w, h, xd, yd, offsets = self.get_extent_offsets(renderer)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/offsetbox.py", line 388, in get_extent_offsets
for c in self.get_visible_children()]
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/offsetbox.py", line 259, in get_extent
w, h, xd, yd, offsets = self.get_extent_offsets(renderer)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/offsetbox.py", line 458, in get_extent_offsets
for c in self.get_visible_children()]
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/offsetbox.py", line 831, in get_extent
bbox, info, d = self._text._get_layout(renderer)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/text.py", line 309, in _get_layout
ismath=ismath)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/backends/backend_agg.py", line 236, in get_text_width_height_descent
s, fontsize, renderer=self)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/texmanager.py", line 501, in get_text_width_height_descent
dvifile = self.make_dvi(tex, fontsize)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/texmanager.py", line 362, in make_dvi
with Locked(self.texcache):
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/cbook/__init__.py", line 2529, in __enter__
raise self.TimeoutError(err_str)
TimeoutError: LOCKERROR: matplotlib is trying to acquire the lock
'/Users/lester/.matplotlib/tex.cache/.matplotlib_lock-*'
and has failed. This maybe due to any other process holding this
lock. If you are sure no other matplotlib process is running try
removing these folders and trying again.
<Figure size 576x576 with 4 Axes>
zeta acceptanceProb 0 6027 211 -21712.897052366243 2.766988273875847 0.0
xi acceptanceProb 0 6028 211 -3872.4710096800995 1.9798069136695102 0.0
zeta acceptanceProb 0 6028 211 -7038.719808084215 2.5979726100714715 0.0
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.7104043859471993 0.0 0.0 0.7996916346305658 0.0 0.0 0.135128341577 1.0 0.608853853301 1.02715151621 0.912060487039 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
eta acceptanceProb 0 6128 231 -940.22460844348 1.107817345498851 0.0
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.0780189121895272 0.0 0.0 1.1299233906903912 0.0 0.0 0.196972510588 1.0 0.508062726456 0.819596726095 0.716056513176 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.8727916263529221 0.0 0.0 0.9464976311560112 0.0 0.0 0.189352319528 1.0 0.504180135158 0.881337040294 0.803962167949 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.8727916263529221 0.0 0.0 0.9464976311560112 0.0 0.0 0.189352319528 1.0 0.510228175263 0.881337040294 0.803962167949 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
6500
6500
6500
6500
xi acceptanceProb 0 6543 211 -1138.4378868806668 2.6385417899896915 0.0
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.6999038929994311 0.0 0.0 0.7589210396651986 0.0 0.0 0.20119818209 1.0 0.500780672484 1.075234888 1.06840901317 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.0239254469178807 0.0 0.0 1.0224498224218956 0.0 0.0 0.250638935633 1.0 0.538627216069 0.715272251754 0.851332759634 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.9579624645304214 0.0 0.0 1.0299658199462483 0.0 0.0 0.261397574313 1.0 0.53017438652 1.00577526013 0.818294036953 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.760446705977602 0.0 0.0 0.8653771966863597 0.0 0.0 0.175552940997 1.0 0.502893793748 0.983208126159 0.865312844743 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
7000
7000
7000
7000
zeta acceptanceProb 0 7022 224 -770.1880701121601 3.4155278667996765 0.0
zeta acceptanceProb 0 7203 224 -833.0709923138598 3.630793432427148 0.0
zeta acceptanceProb 0 7244 224 -749.4055210522627 3.609382853158464 0.0
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.9433874627372739 0.0 0.0 0.9535492727799977 0.0 0.0 0.32831173544 1.0 0.521175575654 1.06920449912 0.847186341311 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
xi acceptanceProb 0 7306 73 -9576.261861585788 1.5167984783143158 0.0
eta acceptanceProb 0 7306 73 -982.0784100841777 2.5773954148262455 0.0
zeta acceptanceProb 0 7306 73 -11751.128109714758 2.5773954148262455 0.0
7500 15000
7500
7500 15000
7500
7500 15000
7500
7500 15000
7500
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.6942467887094136 0.0 0.0 0.7320974059590243 0.0 0.0 0.193330726989 1.0 0.560022585497 0.828246588021 0.723847535572 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.7501006453832143 0.0 0.0 0.819724367453454 0.0 0.0 0.15847619721 1.0 0.501813264018 0.870587966463 0.868493583908 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.8268712287634481 0.0 0.0 0.8778430326338004 0.0 0.0 0.191541497311 1.0 0.543440388235 0.969056216425 0.772253447547 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.9158232116608906 0.0 0.0 0.8970395980629728 0.0 0.0 0.233788670219 1.0 0.508479037033 0.96586210881 0.833460018246 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
eta acceptanceProb 0 7985 260 -987.5515314312602 1.7833072311905762 0.0
8000
eta acceptanceProb 0 7992 260 -2485.773354822697 1.7033196264278203 0.0
eta acceptanceProb 0 7993 260 -1455.2351843372244 2.1234447306372535 0.0
eta acceptanceProb 0 7996 260 -3132.9607121419654 1.8208419464877301 0.0
8000
8000
eta acceptanceProb 0 8002 260 -915.9752945178506 1.1775262183413036 0.0
eta acceptanceProb 0 8005 260 -2090.3168744827726 0.834533948372647 0.0
eta acceptanceProb 0 8006 260 -1781.7789474434792 0.7936915974962415 0.0
8000
eta acceptanceProb 0 8011 260 -1597.1706660851737 3.1571802165102563 0.0
eta acceptanceProb 0 8013 260 -1917.4704772553462 3.295956983425326 0.0
eta acceptanceProb 0 8024 260 -1277.759473960268 3.5877360535298513 0.0
eta acceptanceProb 0 8027 260 -1051.309012435734 3.8427591586096046 0.0
eta acceptanceProb 0 8033 260 -1925.110128181913 3.835032026395849 0.0
eta acceptanceProb 0 8036 260 -1201.3691727715936 3.598166026847527 0.0
eta acceptanceProb 0 8038 260 -785.5631203654723 2.500180638269372 0.0
eta acceptanceProb 0 8046 72 -1097.0923088786767 1.7042923952890532 0.0
eta acceptanceProb 0 8052 260 -1862.4642243586857 4.036997969851522 0.0
eta acceptanceProb 0 8053 260 -1087.22144009504 3.992313564256416 0.0
eta acceptanceProb 0 8065 260 -1097.2638397929095 3.155742908925081 0.0
eta acceptanceProb 0 8074 260 -1140.6081973316261 2.8203458192213735 0.0
eta acceptanceProb 0 8079 260 -1251.5068912624351 4.011842624210485 0.0
eta acceptanceProb 0 8088 260 -1217.097366228503 4.230519787782295 0.0
eta acceptanceProb 0 8108 260 -2055.589947122662 4.032704353905541 0.0
eta acceptanceProb 0 8117 260 -1017.2935712569217 0.8593372609391555 0.0
xi acceptanceProb 0 8204 73 -31638.229446968817 1.3914389826099867 0.0
zeta acceptanceProb 0 8204 73 -30039.805656234395 2.336662056716434 0.0
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.9487671333462149 0.0 0.0 1.0137528739957522 0.0 0.0 0.268480016211 1.0 0.502566774965 0.900716894694 0.863832948288 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.8709340875670627 0.0 0.0 0.9047500439191901 0.0 0.0 0.268480016211 1.0 0.523053131821 0.900716894694 0.863832948288 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
xi acceptanceProb 0 8415 211 -12651.403993353157 0.4331655897958555 0.0
zeta acceptanceProb 0 8415 211 -7216.565081535901 3.4592758608288072 0.0
zeta acceptanceProb 0 8416 211 -35408.84939794765 3.485684381535539 0.0
xi acceptanceProb 0 8417 211 -1764.7271289576006 3.1907809563409986 0.0
zeta acceptanceProb 0 8417 211 -57905.27003948132 4.065142728941436 0.0
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.1448929333548958 0.0 0.0 1.1620884716735795 0.0 0.0 0.297726300121 1.0 0.516794311515 1.02423553445 1.00821661779 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
8500
8500
xi acceptanceProb 0 8501 73 -135683.64135414545 1.7526423490392464 0.0
zeta acceptanceProb 0 8501 73 -5288.1879878508225 3.1383908114762944 0.0
xi acceptanceProb 0 8502 73 -3497.3215759910195 2.0101838981461913 0.0
8500
8500
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.7785421407532337 0.0 0.0 0.8552252787153977 0.0 0.0 0.179077283537 1.0 0.5846271263 1.2012762943 0.796688918561 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.958204103179268 0.0 0.0 0.9710032472743664 0.0 0.0 0.14981116782 1.0 0.622088429619 1.11405307407 0.771821653419 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.0688542850740608 0.0 0.0 1.090777544345387 0.0 0.0 0.228386314987 1.0 0.601161482121 1.02189353913 0.816684815444 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.8448508404283257 0.0 0.0 0.9006575885353935 0.0 0.0 0.213120360549 1.0 0.576426454402 0.932600416046 0.866161740838 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
9000 15000
9000
9000 15000
9000
9000 15000
9000
9000 15000
9000
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.82702525207346 0.0 0.0 0.937434141256246 0.0 0.0 0.142974500222 1.0 0.562717102295 0.98080785236 0.687101861 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.7794720042991907 0.0 0.0 0.9107489306336722 0.0 0.0 0.142974500222 1.0 0.553484682237 0.888454404682 0.687101861 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.7794720042991907 0.0 0.0 0.9107489306336722 0.0 0.0 0.175376396969 1.0 0.542426000822 1.12846516751 0.723625408986 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.8555304022992948 0.0 0.0 0.9569999006795352 0.0 0.0 0.165925617719 1.0 0.501277167365 0.878480361446 0.836203921402 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.8555304022992948 0.0 0.0 0.9569999006795352 0.0 0.0 0.165925617719 1.0 0.555160948837 0.878480361446 0.910407841148 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.8555304022992948 0.0 0.0 0.9569999006795352 0.0 0.0 0.129625632839 1.0 0.540182636888 0.994569855992 0.80944287174 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.8928745712575603 0.0 0.0 0.9506851269386687 0.0 0.0 0.120048738833 1.0 0.522952941595 0.916980114749 0.743877194473 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.8928745712575603 0.0 0.0 0.9506851269386687 0.0 0.0 0.120048738833 1.0 0.580196868941 0.916980114749 0.743877194473 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.8928745712575603 0.0 0.0 0.9506851269386687 0.0 0.0 0.0934132676983 1.0 0.529728011904 0.916980114749 0.743877194473 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.8928745712575603 0.0 0.0 0.9506851269386687 0.0 0.0 0.0865210259483 1.0 0.586425372383 0.920851463245 0.782372824745 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.8928745712575603 0.0 0.0 0.9506851269386687 0.0 0.0 0.0881100924729 1.0 0.528581427217 0.849469201389 0.717250944306 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.8928745712575603 0.0 0.0 0.9506851269386687 0.0 0.0 0.0881100924729 1.0 0.511897664484 0.925959833757 0.757632618386 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.8928745712575603 0.0 0.0 0.9506851269386687 0.0 0.0 0.0881100924729 1.0 0.58715881247 0.781395408677 0.757632618386 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.7223155127484095 0.0 0.0 0.8653815973574387 0.0 0.0 0.0809668724459 1.0 0.515845191607 0.754702801315 0.942195487363 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.7223155127484095 0.0 0.0 0.8653815973574387 0.0 0.0 0.0844113674868 1.0 0.500413986125 1.08598682512 0.754209726304 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.8928745712575603 0.0 0.0 0.9506851269386687 0.0 0.0 0.0943766307918 1.0 0.508062288647 0.777137931708 0.766952619998 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.8928745712575603 0.0 0.0 0.9506851269386687 0.0 0.0 0.0990017091961 1.0 0.514076664831 0.698704530191 0.831366848246 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.8455971578134349 0.0 0.0 0.9303618889790916 0.0 0.0 0.0930541606882 1.0 0.588289071903 0.735673106552 0.831366848246 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.8455971578134349 0.0 0.0 0.9303618889790916 0.0 0.0 0.0929730857561 1.0 0.517777682897 0.735673106552 0.831366848246 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.815876731051644 0.0 0.0 0.8877691626597138 0.0 0.0 0.116735483766 1.0 0.528651535964 0.999154084133 0.704400283131 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.815876731051644 0.0 0.0 0.8877691626597138 0.0 0.0 0.107357274816 1.0 0.510131097758 0.883655158274 0.757031944301 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.815876731051644 0.0 0.0 0.8877691626597138 0.0 0.0 0.107357274816 1.0 0.519896021988 0.901281810325 0.757031944301 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.6988824132116784 0.0 0.0 0.8456886013614711 0.0 0.0 0.0964096127925 1.0 0.510310952106 0.984705466026 0.83163879254 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.6558490328049243 0.0 0.0 0.8137205146245752 0.0 0.0 0.0837214556358 1.0 0.554705052542 1.0008798097 0.760093677705 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.6769252745466571 0.0 0.0 0.830820474163775 0.0 0.0 0.0873600714591 1.0 0.546240486282 0.932305765087 0.776237247045 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.6769252745466571 0.0 0.0 0.830820474163775 0.0 0.0 0.0873600714591 1.0 0.508558557939 0.865395190121 0.735822956813 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.6691702479547746 0.0 0.0 0.8392199004675444 0.0 0.0 0.0818439784539 1.0 0.556493739461 0.920216790462 0.85743246924 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.6691702479547746 0.0 0.0 0.8392199004675444 0.0 0.0 0.0668604647722 1.0 0.519339601151 0.814307681268 0.792313305934 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.6691702479547746 0.0 0.0 0.8392199004675444 0.0 0.0 0.0715607438204 1.0 0.561952877514 0.814307681268 0.792313305934 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.6701989575469534 0.0 0.0 0.8015368057959775 0.0 0.0 0.136864419348 1.0 0.515383414279 1.03565828052 0.882442539863 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.6682869601283213 0.0 0.0 0.7946155172467964 0.0 0.0 0.129631687889 1.0 0.547620345797 0.834331094632 0.780619678655 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.9275281967386808 0.0 0.0 0.9838483978760046 0.0 0.0 0.189336396797 1.0 0.516792288573 0.845323729756 0.836921703597 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.7043292353884228 0.0 0.0 0.8434219168416001 0.0 0.0 0.0996028577175 1.0 0.514599892452 0.925723979267 0.774002781383 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.7508569153165827 0.0 0.0 0.8702283622078358 0.0 0.0 0.0955173265497 1.0 0.512340914089 1.07279488135 0.886594084906 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.986082079680868 0.0 0.0 1.153504559111992 0.0 0.0 0.176556665155 1.0 0.584606436725 0.863827856012 0.695980788574 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.7388342860480352 0.0 0.0 0.8366371192614144 0.0 0.0 0.14151275451 1.0 0.576563749282 0.946621564843 0.979165410893 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.9346594658461513 0.0 0.0 1.0659854502034782 0.0 0.0 0.180791814892 1.0 0.583397809565 0.770039937859 0.710761818869 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.8915247340606697 0.0 0.0 1.0245794071981034 0.0 0.0 0.172542125982 1.0 0.555309197837 0.770039937859 0.670009704568 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.0420528801882434 0.0 0.0 1.1330264866174544 0.0 0.0 0.17359779357 1.0 0.526443360979 0.698825762733 0.670009704568 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
xi acceptanceProb 0 9428 73 -21765.87510823267 3.8155070441965164 0.0
zeta acceptanceProb 0 9428 73 -796.7968266988676 4.013070123701284 0.0
zeta acceptanceProb 0 9429 73 -2445.7203064024943 4.128421669908724 0.0
9500
9500
9500
9500
zeta acceptanceProb 0 9503 205 -2862.1467162608456 0.7862280798659531 0.0
xi acceptanceProb 0 9504 205 -1861.423095531098 1.0231212099966465 0.0
zeta acceptanceProb 0 9504 205 -4212.566325084315 0.9083137914898505 0.0
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.0240379053962987 0.0 0.0 0.9652542466362375 0.0 0.0 0.266791687489 1.0 0.550126402263 0.880281175942 0.814831539586 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.7980301180264017 0.0 0.0 0.8780741973213645 0.0 0.0 0.133235963193 1.0 0.505718832247 1.08008785078 0.859386313915 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
zeta acceptanceProb 0 9731 172 -753.8090068080529 -3.388807405374486 0.0
xi acceptanceProb 0 9767 73 -13654.226448323147 2.776327019238472 0.0
zeta acceptanceProb 0 9780 172 -1343.4636445447293 -1.308650898351819 0.0
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.6714551138902302 0.0 0.0 0.7791514530656569 0.0 0.0 0.142256413493 1.0 0.561812777545 0.780758880258 1.02862446924 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.6714551138902302 0.0 0.0 0.7791514530656569 0.0 0.0 0.136418074319 1.0 0.501019562006 0.780758880258 0.876245179093 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.8009512961530907 0.0 0.0 0.8746972882237303 0.0 0.0 0.169257849621 1.0 0.500110654746 1.25698126284 0.874117672532 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
xi acceptanceProb 0 9970 73 -100734.41724361695 3.568961625936857 0.0
zeta acceptanceProb 0 9970 73 -8503.012355415864 4.011830247099299 0.0
10000
10000
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.9583336719027294 0.0 0.0 0.9811258607868568 0.0 0.0 0.167083740374 1.0 0.534342858881 0.949600193247 0.833798237891 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.9583336719027294 0.0 0.0 0.9811258607868568 0.0 0.0 0.184875930271 1.0 0.504858289604 0.956400057227 0.821009971894 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.9042340247692314 0.0 0.0 0.9648337263614847 0.0 0.0 0.187399803904 1.0 0.511476071922 0.748586825221 0.821009971894 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
10000
10000
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.012257877495894 0.0 0.0 1.1032857432973413 0.0 0.0 0.208440314072 1.0 0.571034682383 0.99273435382 0.84050089987 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
eta acceptanceProb 0 10034 260 -3277.161819719745 3.3611783032944613 0.0
eta acceptanceProb 0 10038 260 -1571.390376672819 2.8776702329881454 0.0
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.729875167314877 0.0 0.0 0.7908414662104224 0.0 0.0 0.21926259129 1.0 0.505889255872 1.41492904556 0.879266586281 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
xi acceptanceProb 0 10230 73 -4407.414926675546 -2.021723055650253 0.0
zeta acceptanceProb 0 10230 73 -7351.813117947478 2.89480009093917 0.0
xi acceptanceProb 0 10231 73 -34964.72099089987 3.0938510922324682 0.0
zeta acceptanceProb 0 10231 73 -12962.254445771681 3.024534614192453 0.0
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.8253800812703422 0.0 0.0 0.8802090745487641 0.0 0.0 0.211293987392 1.0 0.511527789654 1.3471616886 0.810086788861 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
10500 15000
10500
10500 15000
10500
10500 15000
10500
10500 15000
10500
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.9802880160328864 0.0 0.0 0.9858996914978297 0.0 0.0 0.248906626852 1.0 0.510450891683 0.82896246238 0.867517926752 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
zeta acceptanceProb 0 10533 248 -978.2758696930066 2.220318429232857 0.0
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.8276098431897705 0.0 0.0 0.8853273627436189 0.0 0.0 0.184724539732 1.0 0.530596707398 1.35413103667 0.821153359061 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.9351562608786599 0.0 0.0 0.9584650333448208 0.0 0.0 0.281085231114 1.0 0.557148542055 0.902331924205 1.06313286652 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.9351562608786599 0.0 0.0 0.9584650333448208 0.0 0.0 0.275111423897 1.0 0.544602783194 0.902331924205 0.932804644321 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.8556299233248221 0.0 0.0 0.8949720844015173 0.0 0.0 0.206441332618 1.0 0.508685840302 0.735654218193 0.915638597779 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
xi acceptanceProb 0 10907 73 -138144.36581487974 1.8318525839880637 0.0
11000
11000
11000
11000
zeta acceptanceProb 0 11055 32 -901.3811741253454 4.392112940023855 0.0
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.0411447051210776 0.0 0.0 1.1683588458204617 0.0 0.0 0.221106637122 1.0 0.679093837005 0.886350942705 0.748868438583 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.0190944233154882 0.0 0.0 1.1538608046524756 0.0 0.0 0.226312781561 1.0 0.520751516488 0.841547519459 0.867816605111 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
zeta acceptanceProb 0 11104 32 -755.583514879812 1.8801696673575459 0.0
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.0450673165131596 0.0 0.0 1.164526335722486 0.0 0.0 0.238886754061 1.0 0.549834541939 0.704308314945 0.827948040063 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.1220705117766434 0.0 0.0 1.2406559665550108 0.0 0.0 0.227637692508 1.0 0.504605470651 0.711122011109 0.737264320693 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.1098790742727411 0.0 0.0 1.0356012419557064 0.0 0.0 0.283869237607 1.0 0.52969993388 0.640895039595 0.875782785725 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
xi acceptanceProb 0 11278 73 -7379.164281678934 0.8652812458728693 0.0
zeta acceptanceProb 0 11278 73 -9303.30762150363 1.1881332416338821 0.0
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.8983824072075104 0.0 0.0 0.9256625665827453 0.0 0.0 0.274034833042 1.0 0.649271183083 0.76116068224 0.752312316205 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
11500
zeta acceptanceProb 0 11479 248 -757.3865497043611 1.6144243834029743 0.0
11500
11500
11500
zeta acceptanceProb 0 11631 211 -3540.9293625592836 2.4193361660263752 0.0
zeta acceptanceProb 0 11632 211 -24024.85216063058 2.447899017611522 0.0
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.9272787535273078 0.0 0.0 0.953724138361109 0.0 0.0 0.200419374487 1.0 0.550892925119 0.814922295665 0.954306320149 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
xi acceptanceProb 0 11771 73 -3641.5088143698567 1.9126521065003257 0.0
zeta acceptanceProb 0 11771 73 -2877.2261877707524 2.3258752807857643 0.0
eta acceptanceProb 0 11887 72 -769.5203389302745 3.460791023357793 0.0
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.8395143209579615 0.0 0.0 0.8866011132452147 0.0 0.0 0.190394593876 1.0 0.512801858925 1.01176822794 0.812415148625 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
xi acceptanceProb 0 11928 73 -57590.30692247233 3.8952475904346744 0.0
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.7118981957456076 0.0 0.0 1.7238780895201131 0.0 0.0 0.404513733036 1.0 0.532449162851 0.398359304735 0.521913857026 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
xi acceptanceProb 0 11953 73 -11176.613969787777 2.748377075938125 0.0
zeta acceptanceProb 0 11953 73 -1575.1032241609112 2.8198419817469556 0.0
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.7118981957456076 0.0 0.0 1.7238780895201131 0.0 0.0 0.399370249736 1.0 0.648125231392 0.398359304735 0.521913857026 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.7191784106887111 0.0 0.0 1.6735615463500966 0.0 0.0 0.420833733215 1.0 0.599377268029 0.431083982068 0.521913857026 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
12000 15000
12000
12000 15000
12000
12000 15000
12000
12000 15000
12000
Traceback (most recent call last):
File "/opt/anaconda2/lib/python2.7/site-packages/IPython/core/formatters.py", line 334, in __call__
return printer(obj)
File "/opt/anaconda2/lib/python2.7/site-packages/IPython/core/pylabtools.py", line 247, in <lambda>
png_formatter.for_type(Figure, lambda fig: print_figure(fig, 'png', **kwargs))
File "/opt/anaconda2/lib/python2.7/site-packages/IPython/core/pylabtools.py", line 131, in print_figure
fig.canvas.print_figure(bytes_io, **kw)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/backend_bases.py", line 2212, in print_figure
**kwargs)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/backends/backend_agg.py", line 517, in print_png
FigureCanvasAgg.draw(self)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/backends/backend_agg.py", line 437, in draw
self.figure.draw(self.renderer)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/artist.py", line 55, in draw_wrapper
return draw(artist, renderer, *args, **kwargs)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/figure.py", line 1493, in draw
renderer, self, artists, self.suppressComposite)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/image.py", line 141, in _draw_list_compositing_images
a.draw(renderer)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/artist.py", line 55, in draw_wrapper
return draw(artist, renderer, *args, **kwargs)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/axes/_base.py", line 2635, in draw
mimage._draw_list_compositing_images(renderer, self, artists)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/image.py", line 141, in _draw_list_compositing_images
a.draw(renderer)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/artist.py", line 55, in draw_wrapper
return draw(artist, renderer, *args, **kwargs)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/legend.py", line 775, in draw
bbox = self._legend_box.get_window_extent(renderer)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/offsetbox.py", line 266, in get_window_extent
w, h, xd, yd, offsets = self.get_extent_offsets(renderer)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/offsetbox.py", line 388, in get_extent_offsets
for c in self.get_visible_children()]
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/offsetbox.py", line 259, in get_extent
w, h, xd, yd, offsets = self.get_extent_offsets(renderer)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/offsetbox.py", line 458, in get_extent_offsets
for c in self.get_visible_children()]
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/offsetbox.py", line 259, in get_extent
w, h, xd, yd, offsets = self.get_extent_offsets(renderer)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/offsetbox.py", line 388, in get_extent_offsets
for c in self.get_visible_children()]
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/offsetbox.py", line 259, in get_extent
w, h, xd, yd, offsets = self.get_extent_offsets(renderer)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/offsetbox.py", line 458, in get_extent_offsets
for c in self.get_visible_children()]
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/offsetbox.py", line 831, in get_extent
bbox, info, d = self._text._get_layout(renderer)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/text.py", line 309, in _get_layout
ismath=ismath)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/backends/backend_agg.py", line 236, in get_text_width_height_descent
s, fontsize, renderer=self)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/texmanager.py", line 501, in get_text_width_height_descent
dvifile = self.make_dvi(tex, fontsize)
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/texmanager.py", line 362, in make_dvi
with Locked(self.texcache):
File "/opt/anaconda2/lib/python2.7/site-packages/matplotlib/cbook/__init__.py", line 2529, in __enter__
raise self.TimeoutError(err_str)
TimeoutError: LOCKERROR: matplotlib is trying to acquire the lock
'/Users/lester/.matplotlib/tex.cache/.matplotlib_lock-*'
and has failed. This maybe due to any other process holding this
lock. If you are sure no other matplotlib process is running try
removing these folders and trying again.
<Figure size 576x576 with 4 Axes>
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.8268099623542863 0.0 0.0 0.9437613115892594 0.0 0.0 0.185011743829 1.0 0.506114435316 0.781738404135 0.828264570892 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
zeta acceptanceProb 0 12269 211 -3300.5434635245133 4.088609820498082 0.0
zeta acceptanceProb 0 12324 32 -840.672901063105 5.632955614413617 0.0
12500
12500
12500
12500
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.8037748895302474 0.0 0.0 0.880838738509384 0.0 0.0 0.193845731057 1.0 0.594422856793 1.05473846721 0.82664626487 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.8822444707958802 0.0 0.0 0.9408379327975358 0.0 0.0 0.236000512723 1.0 0.583193265006 0.930668207448 0.950851824079 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.8564758581173663 0.0 0.0 0.9489539133125913 0.0 0.0 0.187377639255 1.0 0.54941510534 0.90463572359 0.961480510779 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.740436870153335 0.0 0.0 0.8390456292911878 0.0 0.0 0.207963486645 1.0 0.502973056983 0.984273456554 0.92115323556 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.7961220292637476 0.0 0.0 0.8899803974963105 0.0 0.0 0.170423357905 1.0 0.527290465306 1.12553376449 0.663597164562 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
xi acceptanceProb 0 12705 211 -881.259897861221 0.78935338581854 0.0
zeta acceptanceProb 0 12707 211 -8288.00114022636 1.7119836420003718 0.0
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.7185658671299052 0.0 0.0 0.8789345055108624 0.0 0.0 0.137593978931 1.0 0.601895008086 0.888232732644 0.696671305794 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.6744019899664235 0.0 0.0 0.8619719808943314 0.0 0.0 0.108822811984 1.0 0.51811797539 0.862112799082 0.858660721911 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.6744019899664235 0.0 0.0 0.8619719808943314 0.0 0.0 0.105047469163 1.0 0.582836112181 0.862112799082 0.830624938762 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.6744019899664235 0.0 0.0 0.8619719808943314 0.0 0.0 0.104516284357 1.0 0.605917104606 0.862112799082 0.830624938762 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.6744019899664235 0.0 0.0 0.8619719808943314 0.0 0.0 0.104516284357 1.0 0.521920169447 0.730305060308 0.878995064928 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.6644951802722923 0.0 0.0 0.852040972575708 0.0 0.0 0.0805936170583 1.0 0.5229219357 0.748767603204 0.881442619284 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.6644951802722923 0.0 0.0 0.852040972575708 0.0 0.0 0.0805936170583 1.0 0.55852908351 0.748767603204 0.859448799216 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.6644951802722923 0.0 0.0 0.852040972575708 0.0 0.0 0.0770258055156 1.0 0.528376279379 0.861907215026 0.859448799216 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.6644951802722923 0.0 0.0 0.852040972575708 0.0 0.0 0.0770258055156 1.0 0.504781793652 0.889166331506 0.859448799216 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.7053422800360609 0.0 0.0 0.8756315954508153 0.0 0.0 0.0766470585834 1.0 0.502159109296 0.889166331506 0.805166855951 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.6987301776126624 0.0 0.0 0.8466611497061831 0.0 0.0 0.0775128429418 1.0 0.68312212475 0.889166331506 0.75605125815 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.6925268676543892 0.0 0.0 0.8468332401051698 0.0 0.0 0.0835285025043 1.0 0.541413603399 0.749892602813 0.79822137905 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.7230350801906786 0.0 0.0 0.8665082403258728 0.0 0.0 0.0692702227167 1.0 0.597654430916 0.711596508299 0.783191904734 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.7011610983925833 0.0 0.0 0.8305298338472545 0.0 0.0 0.0908538924024 1.0 0.529083505042 0.711596508299 0.669040485894 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.0809307692922439 0.0 0.0 1.0587152714627635 0.0 0.0 0.350546660296 1.0 0.512637369189 0.699724109356 0.895362050513 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.7381292969534867 0.0 0.0 0.8735376263665827 0.0 0.0 0.14567602635 1.0 0.528049048301 0.754707664272 0.774881719392 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.758957389019039 0.0 0.0 0.8286234738039052 0.0 0.0 0.172045401029 1.0 0.519248638069 1.07419793326 0.627726852322 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
13000
13000
13000
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.776025741590266 0.0 0.0 0.8167098156539941 0.0 0.0 0.177353145889 1.0 0.52152114116 1.02012556274 0.692939979744 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
13000
zeta acceptanceProb 0 13024 61 -776.7317174760061 5.285939633911037 0.0
zeta acceptanceProb 0 13045 61 -1232.705815126329 4.190022364567461 0.0
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.9962375722237282 0.0 0.0 0.983610871489214 0.0 0.0 0.237730181358 1.0 0.504768041836 0.971055610346 0.689849807733 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.669231230154786 0.0 0.0 0.7478397096327212 0.0 0.0 0.245689055717 1.0 0.540041570143 0.909988292238 0.784339287175 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
zeta acceptanceProb 0 13384 248 -854.624847979204 -0.25919887320709095 0.0
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.6658037760790694 0.0 0.0 0.7944983675113878 0.0 0.0 0.166148994995 1.0 0.507672993383 0.804045041801 0.718347501649 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.7064511239078978 0.0 0.0 0.8237089071459783 0.0 0.0 0.128776012399 1.0 0.54154061368 0.956243715839 0.859059114969 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.7510049586308192 0.0 0.0 0.8246279477081168 0.0 0.0 0.160820179766 1.0 0.514824350978 0.880928572302 0.816147058647 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.6934448030671054 0.0 0.0 0.7551308353369207 0.0 0.0 0.154062300549 1.0 0.514746256793 0.871336294674 0.80054098736 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.6935313660274832 0.0 0.0 0.7437530131662954 0.0 0.0 0.163827656149 1.0 0.601310226385 0.91942005504 0.778951302785 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
13500 15000
13500
13500 15000
13500
13500 15000
13500
13500 15000
13500
zeta acceptanceProb 0 13554 248 -770.7487495884868 1.8576102538183425 0.0
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.7420532928106934 0.0 0.0 0.8864232063883236 0.0 0.0 0.179880389232 1.0 0.523851044944 0.993739226816 0.741888391656 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
eta acceptanceProb 0 13618 211 -822.2222271666279 0.5171588905401457 0.0
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.8393792377776021 0.0 0.0 0.923784734495583 0.0 0.0 0.126285717945 1.0 0.524849567588 1.08874353893 0.751063892815 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.8395808359512232 0.0 0.0 0.9009128562638814 0.0 0.0 0.133672392098 1.0 0.536914721811 1.08874353893 0.719974198335 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.6872982779560141 0.0 0.0 0.7820212523037837 0.0 0.0 0.124659709301 1.0 0.504327948109 1.15223118365 0.812963468793 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.676509538430193 0.0 0.0 0.7682585697704741 0.0 0.0 0.146064919896 1.0 0.50841465778 1.14268748873 0.84123604239 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
zeta acceptanceProb 0 13944 224 -767.5511258398717 3.902342321212149 0.0
xi acceptanceProb 0 13936 73 -3059.9041138394396 3.677686991886383 0.0
zeta acceptanceProb 0 13936 73 -1820.8698030871067 3.8180724674391966 0.0
zeta acceptanceProb 0 13937 73 -3670.3382118872814 3.73071104222906 0.0
14000
14000
14000
14000
xi acceptanceProb 0 14017 73 -21154.611032165314 1.2542317958324487 0.0
zeta acceptanceProb 0 14017 73 -1344.51307625627 1.51873174622123 0.0
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.7745591161450142 0.0 0.0 0.8311696671119493 0.0 0.0 0.15310904981 1.0 0.568054047747 1.03356908361 0.793982789346 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.7745591161450142 0.0 0.0 0.8311696671119493 0.0 0.0 0.127105561936 1.0 0.612764600561 0.772316251765 0.793982789346 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.9260895079578256 0.0 0.0 0.8513734347024088 0.0 0.0 0.290087996789 1.0 0.504053239192 1.13482938521 0.777131610729 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.0115068153780076 0.0 0.0 1.0333208386109791 0.0 0.0 0.30667445647 1.0 0.523585041867 0.483602758202 0.802495412519 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.9182650470562045 0.0 0.0 0.9196522683650623 0.0 0.0 0.232399233125 1.0 0.500569881047 0.94517756853 0.968426930008 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
zeta acceptanceProb 0 14286 172 -848.4401974776966 -0.7051982168578914 0.0
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.0161787262645265 0.0 0.0 0.9425098515552565 0.0 0.0 0.356051456649 1.0 0.503812438356 1.30820161717 0.883628673327 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
zeta acceptanceProb 0 14327 172 -770.9582547107245 0.01912839740532235 0.0
eta acceptanceProb 0 14428 260 -755.4512162838259 2.8604238905102886 0.0
zeta acceptanceProb 0 14427 172 -796.067293012628 0.9622139139358536 0.0
14500
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.7747837106764746 0.0 0.0 0.8008865095276234 0.0 0.0 0.200086085355 1.0 0.532460900528 1.00428641603 0.924724592637 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
14500
14500
14500
zeta acceptanceProb 0 14533 172 -999.1696845653022 -0.6090130968985326 0.0
eta acceptanceProb 0 14614 72 -799.3765897224422 1.573285108501295 0.0
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.0776366596315343 0.0 0.0 1.0869480538052145 0.0 0.0 0.2269266868 1.0 0.510030796768 0.868666846509 0.703836899539 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
zeta acceptanceProb 0 14693 32 -865.9058467312 5.044108834154467 0.0
xi acceptanceProb 0 14714 73 -5609.420365593319 0.2608146006949076 0.0
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.8834523257322469 0.0 0.0 0.8934711724004363 0.0 0.0 0.299396930835 1.0 0.507399069399 0.856571473213 0.742094890653 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.452177895147413 0.0 0.0 1.3953348578322935 0.0 0.0 0.432567928022 1.0 0.500175365918 0.548314196354 0.568311227194 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.5498494515335655 0.0 0.0 1.4602919564520538 0.0 0.0 0.500000887966 1.0 0.55663398309 0.460308347964 0.667961387103 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.5498494515335655 0.0 0.0 1.4602919564520538 0.0 0.0 0.492619916354 1.0 0.543765928932 0.33910869561 0.567057716176 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.6497183043087527 0.0 0.0 1.6274988537712645 0.0 0.0 0.431110907986 1.0 0.549744450691 0.592942223389 0.492350991989 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.7316618144268578 0.0 0.0 1.6559386314612314 0.0 0.0 0.451860965417 1.0 0.536421359451 0.494231153629 0.521485741525 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.0170416936310076 0.0 0.0 0.9966523437234583 0.0 0.0 0.243019993889 1.0 0.531042555263 1.0502162457 0.785910719907 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.5661470096033507 0.0 0.0 1.4866199159850062 0.0 0.0 0.509407808634 1.0 0.540314165243 0.392988931151 0.427891527473 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.9005390922630547 0.0 0.0 0.9156116196100091 0.0 0.0 0.2582240867 1.0 0.535511969658 0.906408832365 0.946349515527 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 0.9005390922630547 0.0 0.0 0.9156116196100091 0.0 0.0 0.205903473831 1.0 0.573348389986 0.629137151574 0.889290089182 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.6900295423597387 0.0 0.0 1.4957258727081972 0.0 0.0 0.440750590721 1.0 0.504977648605 0.431890389444 0.390841236866 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.6900295423597387 0.0 0.0 1.4957258727081972 0.0 0.0 0.479572371464 1.0 0.534797031437 0.364124398349 0.446981565025 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.7488882101460559 0.0 0.0 1.6102024143738476 0.0 0.0 0.454681058285 1.0 0.573157026775 0.455035838586 0.530631741377 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.7488882101460559 0.0 0.0 1.6102024143738476 0.0 0.0 0.383400479855 1.0 0.518067644768 0.403598469277 0.530631741377 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.7960625450935717 0.0 0.0 1.633560126255662 0.0 0.0 0.512327170126 1.0 0.514063029844 0.403598469277 0.46432354738 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.8489898868913712 0.0 0.0 1.7131774325449236 0.0 0.0 0.416285905659 1.0 0.563403257533 0.328971986186 0.507099504549 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.8489898868913712 0.0 0.0 1.7131774325449236 0.0 0.0 0.441843724524 1.0 0.754283185969 0.391584742068 0.507099504549 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.6753782879542682 0.0 0.0 1.6043593119072894 0.0 0.0 0.447133248472 1.0 0.518674418144 0.291479062179 0.597236906585 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.8966912203660395 0.0 0.0 1.6972283177012926 0.0 0.0 0.455395353552 1.0 0.600371999086 0.261842471305 0.597236906585 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.7876943161436514 0.0 0.0 1.6066514643223342 0.0 0.0 0.481485228312 1.0 0.585382550141 0.253644626631 0.552908247334 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
15000 15000
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.7501853246803238 0.0 0.0 1.5689896491416353 0.0 0.0 0.534278378363 1.0 0.56644058668 0.292953440194 0.481236414075 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.695830995474257 0.0 0.0 1.5413910448134973 0.0 0.0 0.534278378363 1.0 0.562019589429 0.292953440194 0.481236414075 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.695830995474257 0.0 0.0 1.5413910448134973 0.0 0.0 0.493175691565 1.0 0.507207236101 0.295699718183 0.540788285807 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.695830995474257 0.0 0.0 1.5413910448134973 0.0 0.0 0.552147704273 1.0 0.584839518361 0.291438866723 0.540788285807 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.7061203935094418 0.0 0.0 1.5376957052918416 0.0 0.0 0.552147704273 1.0 0.618738156193 0.291438866723 0.540788285807 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.7061203935094418 0.0 0.0 1.5376957052918416 0.0 0.0 0.552147704273 1.0 0.532580542543 0.291438866723 0.540788285807 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
15000 15000
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.506423496356251 0.0 0.0 1.3902741780469345 0.0 0.0 0.521407890784 1.0 0.675029905771 0.268789298541 0.515451861363 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
prior_all_output == 0: ax3, bx3, s, k, p, m, s 1.6545963186823176 0.0 0.0 1.5112913709479174 0.0 0.0 0.502976082419 1.0 0.541188954876 0.399354928396 0.658179846106 PRIORS 2.5e-10 5e-09 0.2 0.2 0.0 0.1 0.1
acceptanceProb_pbad 1
15000 15000
15000 15000
/Users/lester/Documents/GitHub/kelly_model/scenario29/update_GBeagle_fix/true_constant_alpha/mass_sfr_z_correction/alpha_beta_covprop/random_start_gmm/random_start/bad_gmm_cuts/kelly_MH_GMM_3d_Hogg_constant_beta_constant_alpha.py:1693: RuntimeWarning: invalid value encountered in double_scalars
for key in keys:
Iteration: 15000
Rhat values:
alphaN: 1.2938049011196477 nan nan
beta: 1.119807566434564 nan nan
sig0: 1.392605719937651
k: nan
ximean: 1.0335030397562068
xivar: 0.9999965394229083
pbad: 1.290689347565135
outlier_mean: 1.0800638243007186
outlier_sigma: 1.0653718728741803
_build_chain
In [2]:
In [2]:
In [2]:
In [2]:
In [2]:
In [2]:
In [2]: